Pear Vc

We are a product-focused organization that dreams big and achieves those dreams. Our customers are large players in the construction industry. This is an opportunity to be part of a nimble team where every individual becomes an expert in their area. We work fast, iterate quickly, and create a product that transforms how our customers work through AI.This is the place for you if you’ve worked in a role at the intersection of AI, data analytics, construction tech, construction management, and innovative technology—and you’re looking for the next leap in your career.We’re a growing company backed by Primary Ventures, LDV Capital, Pear VC, and other top investors. You will work directly with the CEO and our customers—large organizations that own and operate hospitals, universities, and public infrastructure. You’ll have the opportunity to shape our data strategy by exploring various data sources and datasets, running exploratory AI models, and providing analytics that support customer decisions. This is a unique chance to join early and shape your career with Gryps.Must Haves<ul><li>Have an undergraduate or Master’s degree in a quantitative field (e.g., mathematics, engineering, statistics, or similar) or construction management</li><li>2+ years of work experience involving quantitative data analysis and complex problem-solving in construction</li><li>Proficiency in SQL and Python, along with experience using Quicksight, Power BI, Tableau, Jupyter Notebook, or other data visualization and exploration tools</li><li>Have 2+ years of construction industry experience</li><li>Possess excellent interpersonal and communication skills</li><li>Are curious, a great listener, and enjoy working with customers to find data-driven ways to support decision-making</li></ul>You would love your job if you:<ul><li>Are customer-obsessed and love helping people apply AI in their workflows</li><li>Are looking to join a small team and grow with it</li><li>Get excited by creating new processes, working with data, and innovating data applications</li><li>Are intrigued by how AI and RPA will change the construction industry</li><li>Love collaborating across teams to solve problems</li><li>Want to grow your career in customer success, data analytics, data science, or machine learning</li><li>Are passionate about disrupting the construction industry with technology</li><li>Are a fast learner or have a deep understanding of technology systems in the construction industry</li><li>Love working with data to uncover patterns and insights</li></ul>What you'll be doing:<ul><li>Understanding customer decision-making and identifying data that can influence those decisions</li><li>Analyzing data structures from construction systems or public data sources</li><li>Setting up customer dashboards, reconfiguring business processes, or leading whiteboard sessions to map out customer data use</li><li>Identifying and proposing potential data sources that could support customer decision-making</li><li>Consulting with customers on how to leverage their data via the Gryps platform</li><li>Documenting data workflows, data policies, structures, standards, and procedures for customer systems</li><li>Developing and running advanced descriptive, predictive, and prescriptive analytics using Jupyter Notebook and Python</li><li>Gathering feedback on current Gryps use cases and identifying new opportunities</li></ul>We recognize you as an early joiner by:<ul><li>Competitive compensation</li><li>Flexible paid time off</li><li>Medical, dental, and vision benefits</li><li>Flexible career path</li><li>Direct influence on our product and company roadmap</li></ul>About the CompanyGryps is a NYC-based, VC-backed early-stage startup on a mission to revolutionize the $10T construction industry by transforming the way data and knowledge are consumed by construction decision-makers.Our Robotic Process Automation and AI-powered platform sets Gryps apart by automatically ingesting, understanding, and augmenting construction data—delivering actionable insights through intelligent applications. Our products have already transformed operations for top hospitals and developers by streamlining construction processes.At Gryps, we foster a culture of innovation, where brilliant minds collaborate to solve complex challenges. Our diverse team of talented engineers and industry experts drives our continuous pursuit of excellence.With an ambitious product roadmap and fresh funding to fuel our growth, Gryps is poised to transform the construction industry. To achieve this vision, we are seeking exceptional professionals to join our dynamic team and help bring our revolutionary ideas to life.Join Gryps today and be a part of reshaping a $10T industry!

Data Analyst (Construction Management) - Gryps

<h2>About Takt</h2>Our Vision: A world where factories think.Takt is building the brains of factories.Factories have spent the last decade digitizing: adding sensors, software, anddashboards everywhere. Yet most factories aren’t meaningfully smarter. Data isfragmented across disconnected systems, locked in reports, and dependent on tribalknowledge living in people’s heads.The hard problem isn’t collecting data, it’s turning it into institutional intelligence.Takt is building the brains of factories. We’re closing the loop from data → information→ insight → action by orchestrating AI agents with deep operational context acrossthe entire manufacturing stack. These systems reason about what’s happening, why it’shappening, and what to do next, acting as a continuous thought partner to factoryleadership across sales, operations, supply chain, and finance.This is not a chatbot or another analytics layer. We’re pushing the frontier of AIreasoning and decision-making in real-world, high-stakes environments. Just as Teslaredefined the car as a software-first system, Takt is redefining manufacturing as asoftware-defined industry.<h3>Funding</h3>Takt is funded by Pear VC (backed Doordash, Gusto) and is part of thePearX accelerator program.Website: <a target="_blank" rel="noopener noreferrer ugc" href="http://www.taktconnect.com">www.taktconnect.com</a><h3>Founders</h3>Takt was founded by Adhitya Raghavan (CEO) and Will Zunker (CTO).Adhitya is from a small village in South India and first learned about factories by workingas an operator on his father’s shop floor. His journey through squash took him toPrinceton (Mechanical &amp;amp; Aerospace Engineering), Harvard (MBA, Baker Scholar), andBain. Now, he’s bringing it full circle, building Takt to solve the very pain he experiencedfirsthand in factories and aiming to put a dent in the $8 trillion of waste that occurs inmanufacturing globally.Will an MIT PhD has deep experience in optimizing manufacturing processes throughphysics-based modeling and AI, driven by a belief that advanced methods canfundamentally transform how things are made. Along the way, he built open-sourcetools and collaborated with engineers across diverse manufacturing sectors, learningfirsthand the challenges of waste and inefficiency on the factory floor. Now, at Takt, he’schanneling that journey into building technology that helps factories run smarter, faster,and with less waste.<h3>Core Cultural Values</h3><ol><li>Stupid enough to make our dreams a reality: We are dreamers who build a better world. We own our decisions. We have the irrational belief and hunger to work until our dreams are a reality</li><li>The last one standing: Every single person takes ownership of their work with a gritty resourcefulness and dares to fight for it with every ounce of their energy.</li><li>Insatiable curiosity: Its always day 1 and we are an empty cup, a dry sponge ready to learn. Approaching every action with humility and scientific rigor and adopting a Kaizen mindset.</li><li>The best F1 team in the stadium: We win together and lose together; every person plays a crucial role to win the race. We have high expectations, trust our teammates and create the environment for everyone to shine. In the path the victory, we celebrate every small professional and personal win cherishing the journey</li></ol><h3>Role</h3>Founding Full Stack Engineer<ul><li>Location: San Francisco, in person 4 to 5 days a week. Open to candidates willing to relocate.</li><li>Hours: 50 to 70 hours per week with space for personal interests</li><li>Compensation: 120-180K</li><li>Equity: To be discussed (0.5-1%)</li><li>Prior experience: 2-3 years minimum</li></ul>You will be the first engineering hire and will work directly with the founders to build thecore intelligence engine that powers modern factories. You will help design, build, anddeploy systems across the entire stack and influence the earliest product, infrastructure,and architecture decisions. This role is for someone who wants deep ownership andreal long-term impact.<h3>Core Technical Requirements</h3><ul><li>Experience deploying and maintain full stack production grade code at scale to support 50-100 enterprise customers with minimal downtime</li><li>Strong cloud infrastructure skills (Azure preferred).</li><li>Deep experience with data pipelines, especially cleaning messy, inconsistent real-world data AI-native in approach to coding utilizing new-age tools (e.g. Claude Code) to develop with speed.</li><li>Strong generalist coding skillset especially on the back-end side.</li></ul><h3>Nice to have</h3><ul><li>Experience shipping production AI/ML or LLM systems end-to-end (not research prototypes).</li><li>Comfortable owning LLM tool orchestration, chain design, agent delegation, prompt engineering, and evaluation methodology.</li><li>Hands-on experience integrating with enterprise systems like ERP, MES, and other data historians (Microsoft Business Central/ SAP)</li><li>Working knowledge of relational + SQL databases</li><li>Familiarity with per missioning models, data governance, or SOC2/GDPR.</li><li>Experience engaging with IT teams and meeting security requirements for enterprise customers.</li></ul><h3>Mindset &amp; Work Style</h3><ul><li>Strong sense of agency and ownership: comfortable making fast decisions and revising them.</li><li>Shipping and moving quickly, makes practical choices, and delivers value to customers</li><li>Willing to learn and can get things done, even if they don’t know it from the get-go</li><li>Thrives with incomplete information</li><li>Passion for the product: speaks their mind, contributes ideas, and pushes for the best solution</li><li>Long-term commitment to the mission, we are building foundational systems, not short-lived features. This means putting in the hours consistently and also making harder short term decisions for long term benefits</li></ul>

Founding Full-Stack Engineer - Takt

About Us: At ResiQuant, we're tackling one of the biggest challenges in disaster resilience: the lack of accurate, standardized, and dynamic property data. In a world increasingly impacted by climate change and natural disasters like earthquakes, hurricanes, and wildfires, decisions about risk are often made with incomplete or incorrect information.Our mission is to empower insurers, financial institutions, and asset managers with AI systems fused with structural engineering expertise. These systems bridge critical data gaps to deliver precise, actionable building insights for better decision-making.Founded by Stanford PhDs, we are committed to leveraging cutting-edge AI to protect communities and businesses from disaster impacts. At ResiQuant, we're building a future where every organization has access to world-class property risk intelligence to drive resilience and safeguard what matters most. The Role You'll expand the structural engineering intelligence that powers AI systems capable of assessing building vulnerability like expert engineers. You will generate ground truth data and define the logical reasoning frameworks that determine how buildings survive natural disasters. Working directly with our Stanford PhD founders and top-tier AI team, you'll create the technical foundation that enables insurers to make billion-dollar risk decisions with unprecedented accuracy, while positioning yourself to lead all engineering and catastrophe modeling expertise as we scale across the US and internationally. What You'll Do<ul><li>Analyze building imagery and varied property documents to create comprehensive datasets that teach AI systems how expert engineers assess structures across different US regions and construction practices.</li><li>Collaborate directly with AI and backend engineering teams to implement your structural expertise in our product to ensure accuracy at scale.</li><li>Support customer success by interacting with insurance customers and handling domain-specific technical questions.</li><li>Define failure modes and vulnerability frameworks for buildings subjected to earthquakes, hurricanes, wildfires, and other natural hazards.</li><li>Review and validate AI-generated structural assessments to continuously improve model accuracy.</li></ul> Who You Are<ul><li>2–6 years of structural engineering consulting experience with existing buildings (retrofit design or forensic investigations preferred).</li><li>BS in Civil/Structural Engineering required. Master's in Structural Engineering preferred.</li><li>Deep knowledge of US building codes, permits, and regional construction practices.</li><li>Technical understanding of building failure modes during disasters.</li><li>AI mindset: excited by AI developments and eager to combine them with structural engineering expertise.</li><li>Thrive in fast-paced, high-ownership environments with a founder mentality.</li><li>Excited to relocate to San Francisco and commit to 5-days in-office collaboration.</li></ul> Nice to Have<ul><li>Catastrophe modeling experience (hurricane, earthquake, severe convective storm, wildfire).</li><li>Functional programming skills in Python.</li><li>Statistics and probability knowledge.</li></ul> Why Join Us<ul><li>Founding Impact: Be a founding engineer shaping how AI transforms risk assessment in the $200B property insurance industry.</li><li>Growth: Work directly with Stanford PhD founders and AI researchers; accelerate your technical and leadership trajectory.</li><li>Innovation: Build at the frontier of AI, structural engineering, climate science, and catastrophe modeling.</li><li>Mission: Protect communities and businesses from disaster impacts.</li></ul> What We Offer<ul><li>Competitive salary + significant equity.</li><li>Full medical, dental, and vision benefits.</li><li>401(k) with company match.</li><li>Daily lunch + commute support in our SF office.</li><li>Fast-paced, mission-driven environment with access to cutting-edge AI and research.</li></ul>

Structural & Disaster Exposure Engineer - ResiQuant

<h2>About NomadicML</h2>Americans drive over 5 trillion miles a year, more than 500 billion of them recorded. Buried in that footage is the next frontier of machine intelligence. At NomadicML, we’re building the platform that unlocks it.Our Vision-Language Models (VLMs) act as the new “hydraulic mining” for video, transforming raw footage into structured intelligence that powers real-world autonomy and robotics. We partner with industry leaders across self-driving, robotics, and industrial automation to mine insights from petabytes of data that were once unusable.NomadicML was founded by Mustafa Bal and Varun Krishnan, who met at Harvard University while studying Computer Science.<ul><li>Mustafa is a core contributor to ONNX Runtime and DeepSpeed with deep expertise in distributed systems and large-scale model training infrastructure</li><li>Varun is an INFORMS Wagner Prize Finalist for his research in large-scale driver navigation AI models and one of the top chess players in the US.</li></ul>Our team has built mission-critical AI systems at Snowflake, Lyft, Microsoft, Amazon, and IBM Research, holds top-tier publications in VLMS and AI at conferences like CVPR, and moves with the speed and clarity of a startup obsessed with impact.<h2>About the Role</h2>We’re seeking a Machine Learning Engineer who thrives at the frontier of foundation-model research and production engineering. You’ll help define how machines learn from motion: training and fine-tuning large-scale Vision-Language Models to reason about complex, real-world video.Your work will involve building multi-modal architectures that perceive, localize, and describe motion events (turns, lane changes, interactions, anomalies) across millions of frames, and turning those breakthroughs into robust APIs and SDKs used by enterprise customers.You’ll work directly with the founders to:<ul><li>Train and evaluate VLMs specialized for motion understanding in autonomous-driving and robotics datasets.</li><li>Design and scale GPU-accelerated pipelines for training, fine-tuning, and inference on multi-modal data (video + language + sensor metadata).</li><li>Build agentic evaluation frameworks that benchmark spatiotemporal reasoning, localization accuracy, and narrative consistency.</li><li>Develop and productionize curation loops that use our own models to generate and refine datasets (“AI training AI”).</li><li>Publish high-impact research (e.g., NeurIPS, CVPR) while shipping features that customers use immediately. </li></ul><h3>You’ll Excel If You Have</h3><ul><li>Strong proficiency in Python, PyTorch, and large-scale ML workflows.</li><li>Research experience in foundation models, VLMs, or multi-modal learning (publications/patents a plus).</li><li>Ability to iterate quickly and autonomously, running experiments end-to-end.</li><li>Experience training or fine-tuning models on video or sensor data.</li><li>Understanding of retrieval systems, embeddings, and GPU optimization.</li></ul><h3>Nice to Have</h3><ul><li>Contributions to open-source ML frameworks (e.g., DeepSpeed, Hugging Face).</li><li>Experience with vector databases, distributed training, or ML orchestration systems (e.g., Ray, Kubeflow, MLflow).</li><li>Prior exposure to autonomous-driving or robotics datasets.</li></ul>

Member of Technical Staff, Machine Learning - NomadicML

About Us:At ResiQuant, we're tackling one of the biggest challenges in disaster resilience: the lack of accurate, standardized, and dynamic property data. In a world increasingly impacted by climate change and natural disasters like earthquakes, hurricanes, and wildfires, decisions about risk are often made with incomplete or incorrect information.Our mission is to empower insurers, financial institutions, and asset managers with AI systems fused with structural engineering expertise. These systems bridge critical data gaps to deliver precise, actionable building insights for better decision-making.Founded by Stanford PhDs, we are committed to leveraging cutting-edge AI to protect communities and businesses from disaster impacts. At ResiQuant, we're building a future where every organization has access to world-class property risk intelligence to drive resilience and safeguard what matters most.<h3>The Role</h3>You will architect and own the backend systems that power AI-driven property risk intelligence at enterprise scale. You’ll design APIs, data pipelines, and model-integrated services that deliver reliable, real-time insights insurers can trust in billion-dollar underwriting decisions. As an early team member, you’ll collaborate closely with the founders to shape both the platform’s technical foundation and how cutting-edge AI is applied safely and effectively in the insurance industry.<h3>What You’ll Do</h3><ul><li>Own backend features end-to-end — from design to deployment.</li><li>Architect scalable services and integrations for Fortune 500 insurers.</li><li>Develop pipelines to ingest, validate, and transform large-scale property datasets.</li><li>Build and optimize AI-assisted backend capabilities (API design, retrieval-backed features, monitoring).</li><li>Ensure observability, reliability, and performance across systems.</li><li>Collaborate with founders, engineers, and customers to iterate quickly on impactful features.</li></ul><h3>Who You Are</h3><ul><li>0–5 years of engineering experience (1–3 years ideal). Exceptional new grads welcome.</li><li>BS in Computer Science or equivalent.</li><li>Skilled in Python, databases, and cloud platforms (AWS/GCP).</li><li>Experience shipping AI-assisted or data-intensive services (e.g., model APIs, retrieval pipelines).</li><li>Proficient with modern AI tools for coding and productivity.</li><li>Thrive in fast-paced, high-stakes environments with strong ownership mentality.</li></ul><h3>Nice to Have</h3><ul><li>PostgreSQL schema design and migration experience.</li><li>Familiarity with observability (logs, metrics, traces) and performance tuning.</li><li>CI/CD pipelines and deployment automation.</li></ul><h3>Why Join Us</h3><ul><li>Founding Impact: Help architect the core backend of a company disrupting the $200B insurance industry.</li><li>Growth: Work directly with experienced engineers and founders; accelerate your technical and leadership skills.</li><li>Innovation: Build AI-driven systems at the intersection of structural engineering, climate science, and finance.</li><li>Mission: Protect communities and businesses from disaster impacts.</li></ul><h3>What We Offer</h3><ul><li>Competitive salary + significant equity.</li><li>Full medical, dental, and vision benefits.</li><li>401(k) with company match.</li><li>Daily lunch + commute support in our SF office.</li><li>Fast-paced, mission-driven environment with access to cutting-edge AI and research.</li></ul>

Pear Vc

Open jobs at Pear Vc

Data Analyst (Construction Management) - Gryps

Founding Full-Stack Engineer - Takt

Structural & Disaster Exposure Engineer - ResiQuant

Member of Technical Staff, Machine Learning - NomadicML

Product Engineer (Backend) - Resiquant AI

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