Browse Data and AI jobs in Netherlands, then compare roles, skills, and adjacent GenAI career paths.

Awin

<p><strong>About the AI Platform Team </strong></p>
<p>The AI Platform Team enables Awin teams to build, ship, and operate AI-powered products safely, consistently, and efficiently.</p>
<p>We focus on the shared platform and enablement layer for AI development across the company. That includes reusable services, internal APIs and SDKs, platform patterns, observability, evaluation support, guardrails, cost visibility, and practical guidance that helps teams move from experimentation to production with confidence.</p>
<p>This is a team for engineers who enjoy building internal platforms, creating paved roads for others, and raising the engineering quality bar for AI development across the organization.</p>
<p><strong>About the role</strong></p>
<p>We are looking for a<strong> Senior AI Platform Engineer - Security &amp; Governance</strong> to join the AI Platform Team and help define and implement the guardrails, privacy patterns, governance mechanisms, and safe defaults that allow AI adoption to scale responsibly across Awin.</p>
<p>In this role, you will work on the safety and control layer of AI development: AI security patterns, privacy and PII handling guidance, provider and model governance, reusable guardrails, and lightweight readiness mechanisms that improve safety without creating unnecessary process.</p>
<p>This role is best suited to someone who combines strong engineering judgment with real practical experience in security, governance, privacy, or compliance for AI-powered systems. We care more about evidence of sound decision-making and pragmatic implementation than about titles or years in a specific niche.</p>
<p><strong>What youʼll do </strong></p>
<ul>
<li>Define and improve practical guardrails and safe defaults for AI-powered systems</li>
<li>Help shape Awinʼs approach to privacy, PII handling, and data-safe patterns for AI workflows</li>
<li>Contribute to approved provider and model guidance, including practical validation and usage expectations</li>
<li>Work with engineers to translate policy, risk, and governance needs into reusable platform patterns and engineering controls</li>
<li>Help define production-ready expectations for AI systems from a safety, governance, and risk perspective</li>
<li>Contribute to readiness checks, automated validations, and scalable governance mechanisms that reduce reliance on manual approval processes</li>
<li>Help improve logging, tracing, and observability practices so AI systems are auditable and safer to operate</li>
<li>Partner closely with Security, Legal, Architecture, and product engineering teams to ensure standards are practical and proportionate</li>
<li>Support teams in understanding AI-specific risks such as unsafe outputs, provider misuse, privacy exposure, and poor trace hygiene</li>
<li>Write clear documentation, patterns, and guidance that help teams apply standards consistently</li>
<li>Contribute to strong engineering practices across the team through clean code, testing, and collaboration </li>
<li>Mentor others and help raise the teamʼs overall maturity in AI safety, governance, and privacy-aware engineering</li>
</ul>
<p><strong>Requirements </strong></p>
<ul>
<li>Strong software engineering fundamentals and experience working on production systems</li>
<li>Practical experience in security, governance, privacy, compliance, or risk-related engineering work</li>
<li>Clear hands-on experience applying those controls to AI- or LLM-powered systems</li>
<li>Strong understanding of AI-specific risks, including privacy exposure, PII handling, unsafe outputs, provider/model risk, and misuse or abuse patterns</li>
<li>Experience translating policy or risk requirements into practical engineering controls, patterns, or defaults</li>
<li>Good understanding of how to make AI systems observable, auditable, and safer to operate in production</li>
<li>Ability to work effectively with engineers, architects, and non-engineering stakeholders such as Security or Legal</li>
<li>Good practical experience with Python and/or JavaScript / TypeScript</li>
<li>Comfortable working across the lifecycle of a platform capability, from design and implementation to rollout and iteration</li>
<li>Good understanding of information security and how to design solutions with security in mind</li>
<li>Comfortable applying unit testing, continuous integration, and continuous deploymentStrong communication skills, both synchronous and asynchronous</li>
<li>Comfortable working through ambiguity and helping shape standards where the right balance between safety and speed is still evolving</li>
<li>Strong judgment and pragmatism, with an ability to improve safety without introducing excessive bureaucracy</li>
</ul>
<p><strong>Nice to have</strong></p>
<ul>
<li>Experience designing or implementing guardrails for AI or LLM-powered systems</li>
<li>Experience with AI governance automation, readiness gates, policy checks, or preflight validation patterns</li>
<li>Familiarity with tracing, auditability, and logging standards for AI systems</li>
<li>Familiarity with evaluation workflows, regression checks, and production readiness practices for AI</li>
<li>Experience assessing third-party AI providers or model usage from a risk or governance perspective</li>
<li> Experience with privacy-by-design patterns in data-sensitive systems</li>
<li>Experience working in regulated or higher-risk environments</li>
<li>Experience writing clear developer guidance and turning repeated risk questions into reusable standards</li>
</ul>
<p><strong>Tools and technologies you may work with:</strong></p>
<ul>
<li>Python</li>
<li>JavaScript / TypeScript</li>
<li>Azure / AWS</li>
<li>LLM APIs</li>
<li>CI/CD tooling</li>
<li>Observability and tracing tools</li>
<li>Policy and validation patterns</li>
<li>Internal platform services, standards, and governance tooling</li>
</ul>
<p><strong>Working style </strong></p>
<p>We are looking for someone who enjoys building in a space that is evolving quickly, but who stays grounded in pragmatic engineering and long-term platform value.</p>
<p>A strong fit for this role is someone who:</p>
<ul>
<li>Thinks clearly about real-world AI risk, not just theoretical concerns</li>
<li>Can balance safety, speed, and developer experience</li>
<li>Communicates clearly and helps others understand trade-offs</li>
<li>Prefers reusable controls and automation over manual gatekeeping</li>
<li>Is comfortable collaborating across engineering, security, architecture, and legal boundaries</li>
<li>Writes clear, actionable guidance rather than vague policy language</li>
<li>Is proactive about identifying risk patterns early and turning them into scalable solutions</li>
<li>Enjoys helping other engineers build safer systems without slowing them down unnecessarily</li>
</ul>
<p></p>
<div><strong>Our Offer</strong></div>
<ul>
<li>
<div><strong>Flexi-Week</strong>: We prioritise your mental health and wellbeing by offering you a four-day Flexi-Week (with one lighter or completely disconnected day per week) at full pay, with no reduction to your annual holiday allowance.</div>
</li>
<li>
<div><strong>Flexi-office</strong>: We offer an international culture and flexibility through our hybrid/remote working scheme which is designed to foster a culture of mutual trust and working flexibility.</div>
</li>
<li>
<div><strong>Work Expense Contribution &amp; Remote Working Furniture</strong>: You will receive a monthly allowance to cover part of your running costs, as well as a furniture package to support you in setting up a comfortable workspace when working from home.</div>
</li>
<li>
<div><strong>Health and Wellbeing</strong>: With our support and access to various initiatives and sports offers, you can focus on your mental and physical wellbeing.</div>
</li>
<li>
<div><strong>Development</strong>: We’ve built our extensive training suite, Awin Academy, to cover a wide range of skills that support your professional and personal growth, with trainings conveniently packaged to help your overall development.</div>
</li>
<li>
<div><strong>Appreciation</strong>: Thank and reward colleagues by sending them a voucher through our peer-to-peer recognition programme.</div>
</li>
</ul>
<div><em>We are hiring in multiple countries for this role. Additional benefits, including health and wellbeing offerings, will be discussed during the initial interview.</em></div>
<p>Established in 2000, Awin is proud of our dynamic, social and inclusive culture.</p>
<p>Like all businesses, we’ve had to adapt and nurture our culture in a virtual environment. Our virtual ‘Life @ Awin’ hub brings our colleagues from across the globe together for various social activities.</p>
<p>Diversity &amp; Inclusion are paramount to us, and we proudly pursue and hire diverse team members. We champion uniqueness and authenticity; this is who we are at our core. Our network of affiliate partnerships are diverse and transparent, as are the employees powering our vision to build the world’s leading open partner ecosystem. We welcome all backgrounds, identities, and experiences. If you need support at any point in the application or interview process, please let us know.</p>
<p><span><span>Awin is part of the Axel Springer group.</span></span> <span><span>Learn more at </span></span><a href="https://www.axelspringer.com/en/" target="_blank" rel="noopener noreferrer ugc"><span><span>axelspringer.com/</span><span>en</span><span>/</span></span></a><span><span>, and explore the Axel Springer Essentials here:</span></span> <a href="https://www.axelspringer.com/en/inside/the-essentials-what-we-have-adapted-and-why" target="_blank" rel="noopener noreferrer ugc"><span><span>axelspringer.com/en/inside/the-essentials-what-we-have-adapted-and-why</span></span></a><span><span> </span></span><span> </span></p>
<p>Apply now to begin the next stage of your career at a progressive company that supports both your professional and personal development.</p>
<p><span>#LI-RS1</span></p>

Senior AI Engineer (f/m/d)

Reddit

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<div>Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit <a href="http://www.redditinc.com/" target="_blank" rel="noopener noreferrer ugc">www.redditinc.com</a>.</div>
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</div></div><p><strong>Location: </strong>Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.</p>
<p><strong>Team Overview</strong></p>
<p>We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch &amp; realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management.</p>
<p>We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems.</p>
<p>This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive.</p>
<p><strong>What You’ll Do</strong></p>
<ul>
<li>Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage.</li>
<li>Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use.</li>
<li>Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning</li>
<li>Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.</li>
<li>Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management</li>
<li>Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives.</li>
</ul>
<p><strong>What You Bring</strong></p>
<ul>
<li>3+ years in data infrastructure/platform engineering or ML infrastructure platforms.</li>
<li>Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools.</li>
<li>Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies.</li>
<li>Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving.</li>
<li>Strong coding skills and ability to write clean, maintainable, well-tested code.</li>
<li>Experience building intelligent automation or agentic workflows for ML systems is a strong plus</li>
<li>Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a plus</li>
</ul>
<p><strong>Benefits:</strong></p>
<ul>
<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>
<li>Family Planning Support</li>
<li>Gender-Affirming Care</li>
<li>Mental Health &amp; Coaching Benefits</li>
<li>Private Pension plan with Employer-matching</li>
<li>100% employer-sponsored group medical plan  </li>
<li>Income Replacement Programs</li>
<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>
<li>Generous Paid Parental Leave</li>
</ul><div><p>In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.</p>
<p><span>During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our <a href="https://redditinc.com/policies/candidate-privacy-policy" rel="noopener noreferrer ugc" target="_blank">Candidate Privacy Policy for Potential Employees and Contractors</a>.</span></p>
<p><em><span>Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</span></em></p></div>

Machine Learning Systems Engineer, Ads ML Platform

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<div>Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit <a href="http://www.redditinc.com/" target="_blank" rel="noopener noreferrer ugc">www.redditinc.com</a>.</div>
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</div></div><p><strong>Location: </strong>Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.</p>
<p>The <strong>Ads Foundational Representations (AFR)</strong> team develops signals and representations of Reddit’s core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with. </p>
<p>Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas:</p>
<ul>
<li><strong>Multimodal &amp; Content Embeddings</strong> - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space. </li>
<li><strong>Contextual and Behavioral Relevance </strong>- Working with Product &amp; Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance.</li>
<li><strong>Knowledge Graph Embeddings - </strong>Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting &amp; business insights. </li>
<li><strong>User Intent Modeling -</strong> Leveraging various techniques to introduce user representations based on the content they interact with: batch &amp; real-time sequence modeling, LLM summarization, etc. </li>
<li><strong>LLM-based Representations</strong> - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes</li>
</ul>
<p>The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization.</p>
<p>As a <strong>Staff ML Engineer</strong>, you’ll be in charge of setting the technical direction of multiple pillars the team owns. You will lead cross-functional ML projects end to end - from high-level business gap analysis to engineering execution. </p>
<p>Roughly 50% of your time will be spent on technical leadership and mentorship (driving strategy &amp; designs, cross-functional collaboration, raising the quality bar), another 50% being individual hands-on work (data analysis &amp; engineering, modeling &amp; automation).  </p>
<p><strong>Responsibilities</strong></p>
<ul>
<li>Providing technical leadership and mentorship to MLEs in the team: driving designs &amp; their review, establishing best practices in analysis, modeling and engineering, keeping the bar high. </li>
<li>Working closely with team/org leadership developing technical strategy for content-based embeddings &amp; relevance for Ads.</li>
<li>Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models.  </li>
<li>Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings. </li>
<li>Building data processing and inference pipelines for the models we develop. </li>
<li>Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments. </li>
<li>Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.</li>
<li>Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance.</li>
<li>Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions.</li>
</ul>
<p><strong>Required Qualifications:</strong></p>
<ul>
<li>7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.</li>
<li>Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects: from requirements, design to cross-team/functional alignment and execution without direct people-management authority. </li>
<li>Excellent communication skills, with the ability to translate complex technical concepts to different audiences, both verbally and in writing. </li>
<li>Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them. </li>
<li>Established data-driven approach for ML system development. Excitement about working with data and readiness to look behind the metric numbers. </li>
<li>Familiarity with the Ads domain and/or Search/Recommender systems.</li>
<li>Experience with mainstream DL frameworks: PyTorch or TensorFlow.</li>
</ul>
<p><strong>Preferred Qualifications:</strong></p>
<ul>
<li>Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP)</li>
<li>Tech leadership experience: mentoring junior engineers and leading complex projects. </li>
<li>Hands-on experience with using/fine-tuning/building LLMs.</li>
</ul>
<p><strong>Benefits:</strong></p>
<ul>
<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>
<li>Family Planning Support</li>
<li>Gender-Affirming Care</li>
<li>Mental Health &amp; Coaching Benefits</li>
<li>Private Pension plan with Employer-matching</li>
<li>100% employer-sponsored group medical plan  </li>
<li>Income Replacement Programs</li>
<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>
<li>Generous Paid Parental Leave</li>
</ul><div><p>In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.</p>
<p><span>During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our <a href="https://redditinc.com/policies/candidate-privacy-policy" rel="noopener noreferrer ugc" target="_blank">Candidate Privacy Policy for Potential Employees and Contractors</a>.</span></p>
<p><em><span>Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</span></em></p></div>

Senior Machine Learning Engineer, Ads Foundational Representations

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<div>Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit <a href="http://www.redditinc.com/" target="_blank" rel="noopener noreferrer ugc">www.redditinc.com</a>.</div>
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</div></div><p><strong>Location: </strong>Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.</p>
<p><strong>About the Team</strong></p>
<p>The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem.</p>
<p><strong>Responsibilities</strong></p>
<ul>
<li>Design and build systems that improve the efficiency of ML training and inference workloads.</li>
<li>Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.</li>
<li>Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.</li>
<li>Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.</li>
<li>Build benchmarking frameworks and performance dashboards for training and serving systems.</li>
<li>Optimize distributed training infrastructure, data pipelines, and model serving architectures.</li>
<li>Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.</li>
<li>Drive technical strategy for ML platform scalability, reliability, and cost efficiency.</li>
</ul>
<p><strong>Qualifications</strong></p>
<p><strong>Required</strong></p>
<ul>
<li>BS, MS, or PhD in Computer Science or a related field.</li>
<li>5+ years of software engineering experience.</li>
<li>Strong proficiency in Python</li>
<li>Profiency in at least one systems language (Go, C++, Rust, or Java) preferred</li>
<li>Experience building distributed systems at scale.</li>
<li>Experience with machine learning infrastructure, training systems, or model serving platforms.</li>
<li>Deep understanding of performance engineering and systems optimization.</li>
<li>Strong debugging and profiling skills.</li>
</ul>
<p><strong>Preferred</strong></p>
<ul>
<li>Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.</li>
<li>Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark</li>
<li>Familiarity with GPU architectures and performance analysis tools.</li>
<li>Experience optimizing cloud infrastructure costs across large ML workloads.</li>
<li>Contributions to internal platforms used by multiple ML teams.</li>
<li>Experience with building real time ML inference applications</li>
</ul>
<p><strong>What Success Looks Like</strong></p>
<ul>
<li>ML engineers can move from idea to experiment faster.</li>
<li>Training and inference costs decrease, performance increases, while model quality is maintained or improved.</li>
<li>GPU utilization and cluster efficiency increase.</li>
<li>Platform reliability improves as ML workloads scale.</li>
<li>Teams spend less time managing infrastructure and more time building models.</li>
<li>Average recommendation model size increases.</li>
</ul>
<p><strong>Benefits:</strong></p>
<ul>
<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>
<li>Family Planning Support</li>
<li>Gender-Affirming Care</li>
<li>Mental Health &amp; Coaching Benefits</li>
<li>Private Pension plan with Employer-matching</li>
<li>100% employer-sponsored group medical plan  </li>
<li>Income Replacement Programs</li>
<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>
<li>Generous Paid Parental Leave</li>
</ul><div><p>In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.</p>
<p><span>During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our <a href="https://redditinc.com/policies/candidate-privacy-policy" rel="noopener noreferrer ugc" target="_blank">Candidate Privacy Policy for Potential Employees and Contractors</a>.</span></p>
<p><em><span>Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</span></em></p></div>

Staff Machine Learning Engineer, ML Efficiency 

Databricks

<p>RDQ127R176</p>
<p>At Databricks, we are passionate about <span>enabling data teams to solve</span> the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to <span>tackle</span> technical challenges, from designing next-gen UI/UX for <span>interfacing</span> with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.</p>
<p>Our engineering teams build highly technical products that fulfill real, important needs in the world. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.</p>
<p>Unity Catalog is our platform native unified and open governance for data and AI. It eliminate silos, simplify governance and accelerate insights at scale. We are looking for a Senior Staff Software Engineer to come tech lead Unity Catalog Runtime Enforcement. We build and harden the runtime enforcement layer for Unity Catalog, ensuring secure, consistent authorization and data access across Databricks compute, engines, and clouds. This reduces incidents and simplifies customer choices by unifying enforcement semantics. </p>
<p><strong>The impact you will have: </strong></p>
<ul>
<li>Lead and grow and engineering team delivering runtime enforcement outcomes in a high-severity, cross-org domain; establish scope, SLAs, and phased roadmaps.</li>
<li>Establish single-source-of-truth scope, operating model, and durable mechanisms for enforcement.</li>
<li>Lead multi-year, multi-team initiatives that shape how Databricks enforces Unity Catalog at runtime across compute types and engines.</li>
<li>Introduce tools to allow greater automation and operability of services.</li>
<li>Use your deep experience to help prevent and investigate production issues.</li>
<li>Plan and lead complicated technical projects that work with several teams within the company.</li>
<li>Contribute as a technical team lead by mentoring others, lead sprint planning, delegating work and assignments to team members and participate in project planning.</li>
</ul>
<p><strong>What we look for:</strong></p>
<ul>
<li>15+ years industry experience building and supporting large-scale distributed systems.</li>
<li>Comfortable working towards a multi-year vision with incremental deliverables.</li>
<li>Extensive experience building and maintaining distributed systems.</li>
<li>Security first mindset.</li>
<li>Cross-org leadership in ambiguous, incident-heavy environments; disciplined rollout and ops maturity.</li>
<li>Motivated by delivering customer value and impact.</li>
<li>Experience driving company initiatives towards customer satisfaction.</li>
<li>BS/MS/PhD in Computer Science or related majors, or equivalent experience.</li>
<li> </li>
</ul><div><p><strong>About Databricks</strong></p>
<p><span>Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&amp;T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on <a href="https://www.linkedin.com/company/databricks" rel="noopener noreferrer ugc" target="_blank">LinkedIn</a>, <a href="https://x.com/databricks" rel="noopener noreferrer ugc" target="_blank">X</a>, <a href="https://www.youtube.com/@Databricks" rel="noopener noreferrer ugc" target="_blank">YouTube</a>, and <a href="https://www.instagram.com/databricksinc/?hl=en" rel="noopener noreferrer ugc" target="_blank">Instagram</a>.<br /><br /><strong>Benefits<br /><br /></strong></span>At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing" rel="noopener noreferrer ugc" target="_blank">here</a>.<br /><br /></p>
<p><strong>Our Commitment to Diversity and Inclusion</strong></p>
<p>At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.</p>
<p><strong>Compliance</strong></p>
<p><strong><span>If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</span></strong></p>
<p><a href="https://www.databricks.com/legal/applicant-privacy-notice" target="_blank" rel="noopener noreferrer ugc"><strong><span>Applicant Privacy Notice</span></strong></a></p></div>

Senior Staff Software Engineer - Unity Catalog Runtime Enforcement 

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