Quantco 

<div>Our AI team operates at the intersection of quantitative decision-making and frontier model technology to create real-world impact in the world's foremost companies. They design, build, and implement applied AI systems that improve the quality of human decisions and unlock major efficiencies. The team collaborates with software engineers and data scientists to solve complex problems in inference optimization, scalable systems design, and human-computer interaction. They combine technical deep learning, business acumen, and engineering expertise with an entrepreneurial mindset driven by rapid experimentation, first-principles thinking, and a passion for tackling complex real-world problems to deliver lasting impact.</div><div><br /></div><div>As an applied scientist intern, you will identify the most impactful problems to solve, translating commercial objectives into technical solutions. You will combine and transform large multimodal datasets to run in-depth statistical analysis, and apply deep learning models to automate large-scale decisions, integrated into live business processes, designed to generate tangible economic impact<i>.</i></div>
<h2>We are looking for team players who have excellent quantitative abilities and:</h2><ul><li>A degree in computer science, mathematics, statistics, physics, economics, or similar fields from a leading university</li><li>In-depth understanding of mathematical and statistical concepts behind the most common machine learning techniques</li><li>Familiarity with frontier lab APIs (Gemini, OpenAI, Anthropic), and their advanced features like structured outputs and tool calling</li><li>Understanding of LLM inference considerations e.g. input vs. output tokens, prompt caching</li><li>Experience working with deep learning models within natural language processing or computer vision (e.g. HuggingFace model import/fine-tuning /inference)</li><li>Experience writing code in Python </li><li>Experience and willingness to work through the challenges associated with large, unstructured, real-world data sets in a client-facing setting</li><li>Ability to see solutions and opportunities that others do not see</li><li>High level of commitment and reliability, good balance of pragmatism and perfectionism</li></ul>
<h2>Bonus if skilled in any of the following tools and/or languages:</h2><ul><li>Cloud Infrastructure</li><li>Git</li></ul>

AI Applied Scientist Intern

<div><span>AI engineers at QuantCo build cutting-edge systems that bridge the gap between advances in frontier model technology and real-world impact in the world's foremost companies. They design, build, and implement applied AI systems that improve the quality of human decisions and unlock major efficiencies. AI engineers work with data scientists to solve complex problems in inference optimization, scalable systems design, and human-computer interaction. Team members may work in forward-deployed roles, collaborating directly with clients to discover, rapidly iterate on and deploy AI solutions, as well as in centralized roles that abstract successful solutions into scalable assets. Our team combines technical deep learning and engineering expertise with an entrepreneurial mindset driven by rapid experimentation, first-principles thinking, and a passion for tackling complex real-world problems to deliver lasting impact.</span></div>
<div> </div>
<div><strong>Description</strong></div>
<div><span>You will design, test, and deploy AI systems that are embedded at scale. Operating at the intersection of machine learning and engineering, you will leverage cutting-edge models to build robust, production-ready AI applications. You will lead the design of data and inference pipelines, orchestrate the integration of LLM-based components such as retrieval-augmented generation (RAG), and balance engineering constraints with business priorities. From system design to deployment, you will own all stages of product iteration and development, building solutions that seamlessly integrate into enterprise settings, designed to change the way our clients work with AI. </span></div>
<h2>Requirements</h2><ul><li>BSc, MSc or PhD in Computer Science, Engineering, Physics, or a related technical or STEM field from a leading university. </li>
<li>Experience working with relevant models and/ or architectures within the following fields: Computer Vision, Natural Language Processing, or Graph Neural Networks.</li>
<li>Experience programming in Python.</li>
<li>Familiarity with the frontier labs APIs (Gemini, OpenAI, Anthropic), and their advanced features like structured outputs and tool calling.</li>
<li>Understanding of LLM inference considerations e.g. input vs. output tokens, prompt caching.</li>
<li>Strong computer science fundamentals in areas such as data structures, cloud infrastructure, distributed systems, machine learning, and high-performance computing.</li>
<li>Experience and willingness to work through the challenges associated with large, unstructured, real-world data sets.</li></ul>

AI Engineering Intern

<div><span>AI engineers at QuantCo build cutting-edge systems that bridge the gap between advances in frontier model technology and real-world impact in the world's foremost companies. They design, build, and implement applied AI systems that improve the quality of human decisions and unlock major efficiencies. AI engineers work with data scientists to solve complex problems in inference optimization, scalable systems design, and human-computer interaction. Team members may work in forward-deployed roles, collaborating directly with clients to discover, rapidly iterate on and deploy AI solutions, as well as in centralized roles that abstract successful solutions into scalable assets. Our team combines technical deep learning and engineering expertise with an entrepreneurial mindset driven by rapid experimentation, first-principles thinking, and a passion for tackling complex real-world problems to deliver lasting impact.</span></div>
<div> </div>
<div><strong>Description</strong></div>
<div><span>You will design, test, and deploy AI systems that are embedded at scale. Operating at the intersection of machine learning and engineering, you will leverage cutting-edge models to build robust, production-ready AI applications. You will lead the design of data and inference pipelines, orchestrate the integration of LLM-based components such as retrieval-augmented generation (RAG), and balance engineering constraints with business priorities. From system design to deployment, you will own all stages of product iteration and development, building solutions that seamlessly integrate into enterprise settings, designed to change the way our clients work with AI. </span></div>
<h2>Requirements</h2><ul><li>BSc, MSc or PhD in Computer Science, Engineering, Physics, or a related technical or STEM field from a leading university. </li>
<li>Experience working with relevant models and/ or architectures within the following fields: Computer Vision, Natural Language Processing, or Graph Neural Networks.</li>
<li>Experience writing production-ready code.</li>
<li>Experience programming in Python. </li>
<li>Familiarity with the frontier labs APIs (Gemini, OpenAI, Anthropic), and their advanced features like structured outputs and tool calling.</li>
<li>Understanding of LLM inference considerations e.g. input vs. output tokens, prompt caching.</li>
<li>Strong computer science fundamentals in areas such as data structures, cloud infrastructure, distributed systems, machine learning, and high-performance computing.</li>
<li>Experience and willingness to work through the challenges associated with large, unstructured, real-world data sets.</li>
<li>Ability to develop custom tooling for efficient experimentation and evaluation of LLM applications / agentic workflows</li></ul>

AI Engineer

<div>Our AI team operates at the intersection of quantitative decision-making and frontier model technology to create real-world impact in the world's foremost companies. They design, build, and implement applied AI systems that improve the quality of human decisions and unlock major efficiencies. The team collaborates with software engineers and data scientists to solve complex problems in inference optimization, scalable systems design, and human-computer interaction. They combine technical deep learning, business acumen, and engineering expertise with an entrepreneurial mindset driven by rapid experimentation, first-principles thinking, and a passion for tackling complex real-world problems to deliver lasting impact.</div><div><br /></div><div>As an applied scientist, you will identify the most impactful problems to solve, translating commercial objectives into technical solutions. You will combine and transform large multimodal datasets to run in-depth statistical analysis, and apply deep learning models to automate large-scale decisions, integrated into live business processes, designed to generate tangible economic impact<i>.</i></div>
<h2>We are looking for team players who have excellent quantitative abilities and:</h2><ul><li>A degree in computer science, mathematics, statistics, physics, economics, or similar fields from a leading university</li><li>In-depth understanding of mathematical and statistical concepts behind the most common machine learning techniques</li><li>Familiarity with frontier lab APIs (Gemini, OpenAI, Anthropic), and their advanced features like structured outputs and tool calling</li><li>Understanding of LLM inference considerations e.g. input vs. output tokens, prompt caching</li><li>Experience working with deep learning models within natural language processing or computer vision (e.g. HuggingFace model import/fine-tuning /inference)</li><li>Experience writing code in Python </li><li>Experience and willingness to work through the challenges associated with large, unstructured, real-world data sets in a client-facing setting</li><li>Ability to see solutions and opportunities that others do not see</li><li>High level of commitment and reliability, good balance of pragmatism and perfectionism</li></ul>
<h2>Bonus if skilled in any of the following tools and/or languages:</h2><ul><li>Cloud Infrastructure</li><li>Git</li></ul>

AI Applied Scientist

<div><span>Data Scientists at QuantCo will learn what it takes to create impact from data: identifying the right framework to translate a business question into a statistical problem; locating and combining data sources as well as transforming large datasets; running in-depth analyses; building machine learning models that automate large-scale decisions and integrating them into live business processes; and interpreting, visualizing, and communicating results to internal and external stakeholders.</span></div>
<h2>We are looking for team players who have excellent quantitative abilities and:</h2><ul><li>A degree in economics, statistics, mathematics, computer science, engineering, physics, or similar fields at a leading university </li><li>In-depth understanding of mathematical and statistical concepts behind most common machine learning techniques and an interest in causal inference</li><li>Experience in coding and working with data (from a previous research or industry internship or extensive course projects) </li><li>Ability to see solutions and opportunities that others do not see</li><li>High level of commitment and reliability, good balance of pragmatism and perfectionism</li></ul>
<h2>Bonus if skilled in any of the following tools and/or languages:</h2><ul><li>SQL</li><li>Tensorflow</li><li>Git</li><li>Cloud infrastructure</li></ul>

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