Research Engineer Intern in New York

Salary range - $250k - $350k | Equity - up to 0.5% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Research Engineer to own problems end to end across our models, inference service, and product. You won't just train a model and hand it off. You'll take it from training through benchmarking, into our inference stack, and work with the team to integrate it into our products. We're a small team that has shipped the current state of the art OCR model, Chandra. Our models collectively have 70k+ Github stars. Our tools are used internally at frontier AI labs like Anthropic, and Fortune 500 enterprises like Siemens. Our team focuses on training small, efficient models that outperform much larger LLMs on domain-specific tasks (like OCR, structured extraction, tables). We move fast, prioritize practical results, and build tools that are open, reproducible, and built to last. You'll test hypotheses quickly, iterate on results, and balance experimental rigor with shipping to customers. Day to day: A typical project might look like: identify a gap in extraction quality on long documents, train and benchmark a new model, optimize it for inference, and work with the team to ship it to users. Concretely: Train and evaluate models: Train task-

About Us: YipitData is the leading market research and analytics firm for the disruptive economy and recently raised up to $475M from The Carlyle Group at a valuation over $1B. We analyze billions of alternative data points every day to provide accurate, detailed insights on ridesharing, e-commerce marketplaces, payments and more. Our on-demand insights team uses proprietary technology to identify, license, clean and analyze the data many of the world’s largest investment funds and corporations depend on. For three years and counting, we have been recognized as one of Inc’s Best Workplaces . We are a fast-growing technology company backed by The Carlyle Group and Norwest Venture Partners. Our offices are located in NYC, Austin, Miami, Denver, Mountain View, Seattle , Hong Kong, Shanghai, Beijing, Guangzhou, and Singapore. We cultivate a people-centric culture focused on mastery, ownership, and transparency. About the Role: This is a hybrid role based in our New York City headquarters. Employees are expected to work from the NYC office three days per week. We expect East Coast working hours. As Our IT Delivery Engineer, You Will: Design, implement, and maintain the systems and platforms that support the company’s internal IT environment Administer and troubleshoot SaaS platforms and endpoint management systems including Kandji, Google Workspace, Okta, Slack, Zoom, and other core business tools Manage and improve device management and endpoint configuration across the global fleet using MDM platforms Partner with Security and Infrastructure teams to ensure systems meet company security and compliance standards Lead and contribute to IT infrastructure and service delivery improvement projects that increase system reliability and operational efficiency Evaluate and implement new technologies that enhance IT service delivery, system management, and automation Develop automation and tooling to streamline provisioning, configuration management, and operational workflows Ma

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role We are looking for customer-focused software engineers to build effective custom software that leverages OpenAI’s APIs to solve real customer problems. As an FDSWE, you will work with our customers and OpenAI Forward Deployed Engineers to design and implement scalable solutions that solve their most difficult problems. You will design abstractions to solve customer problems, and then use them to scale our speed and quality of delivery across all Forward Deployed engagements. You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also work with our Research and Applied Product and Engineering teams to provide insightful customer feedback. This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Embed deeply with strategic customers to understand their business challenges and technical requirements in detail. Design, architect, and develop full-stack solutions using an experiment-driven, iterative approach. Prepare detailed scopes of work and project plans for both proof-of-concept prototypes and full production deployments. Work hands-on with customers' technical teams as a technical expert and trusted advisor, coding side-by-side to drive projects to completion on their infrastructure. Collaborate with Product, Research and Applied teams to ensure seamless customer experiences, project success and actionable product feedback Contribute to internal knowledge bases, codifying best practices and sharing insights gained from customer engagements to scale the Forward Deployed Engineering function. You’ll thrive in this role if

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions. Responsibilities: Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality Building and maintaining automated pipelines that will enforce the correctness of code examp

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Large Language Models (LLMs) continue to push the boundaries of what AI systems can do — but inference is still the bottleneck. The Model Efficiency team is responsible for pushing the limits of LLM inference efficiency across our foundation models. We explore and ship breakthroughs across the model execution stack, including: model architecture and MoE routing optimization decoding and inference-time algorithm improvements software/hardware co-design for GPU acceleration performance optimization without compromising model quality Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. As a Staff Research Engineer, you will develop, prototype, and deploy techniques that materially improve how fast and efficiently our models run in production. You may be a good fit

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Research Engineer in our Safety team, you will play a key role in helping develop safer, more secure, and more reliable models. Your primary focus will be on building tools to enable easy data synthesis, analysis, and management, for complex combinations of real and synthetic data that is used in both model training and evaluation. You will own the cohesive vision of these tooling repositories. You will work closely with a team of research scientists and engineers to create tooling that enables tighter experimentation cycles, better data coverage of the real world, and more scientific rigour. You will have a lot of autonomy and need to be opinionated about what areas of the codebase need elegance and standards, and where that would be overengineering. You will be given high level experimental problems that need to be solved with efficient pipelines, and design and implement the solutions. Your data analysis will collaboratively feed into modelling decisions and experimentation. This role combines expertise in software engineering, statistics, and data science. If any of these topics sound interesting t

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid’s network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you’ll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid’s network. As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You’ll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you’ll translate promising research into production-ready solu

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a Design Engineer at Ramp, you sit at the intersection of design and front-end engineering. You bring ambitious ideas to life in real interfaces, prototype directly in code, validate with customers, and ship production experiences with a high bar for craft, performance, and reliability. Design at Ramp is AI first and builder led. Work starts in an LLM to clarify intent and constraints, moves into tools like Claude and Cursor to explore and build, is tested with real customers, and then comes into Figma for systems and polish. AI and self-serve research are default parts of the workflow, not side experiments. We are looking for multiple design engineers who think like a designer, code like a front-end engineer, and treat AI as a real collaborator. What You’ll Do Design and build high-craft product experiences: Own key surfaces end to end, from concept through production. Use layout, interaction, and motion to make complex behavior feel simple and safe. Work AI first with Cursor and Claude Code: Use LLMs, Cursor, and Claude Code as y

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

About Us: Blockworks is an information platform that sits at the center of the crypto industry. We transform raw, complex data and facts into actionable research, trusted alpha-driven insights, and world-class events. The result is transparency and confidence. Blockworks connects investors and businesses in onchain capital markets. We give businesses a platform to earn trust and provide investors with the information they need to underwrite the asset class. Who You Are: Software engineering is your passion, and you have special talents focused on data architecture, design, and API development. You are a player-coach and a natural leader who understands the technical and human elements that go into great software design. You have a results-oriented attitude and a passion for delivering flawless releases and developing digital product pipelines (CI/CD pipelines). You have a proven track record facilitating engineering teams to increase productivity and quality. You're excited at the possibility of helping design and develop our data pipelines as well as leading our data-related projects and strategies for Blockwork's suite of projects. You love moving quickly in a fast-paced start-up, but you also bring intentionality, sustainability and scalability to your approach as an engineer. What You’ll Do: As our Senior Data Engineer , you will be directly responsible for leading the creation and execution of our data models and strategies that feed our products. You'll work collaboratively with other members of the engineering team to design, develop, implement, and evolve our data pipeline and approaches. Every day will look a little different, but in general, you will do things like: Own Data Sourcing Pipelines: You'll be responsible for helping to architect our data warehousing, ingestion and sourcing strategy, working with multiple SDKs to aggregate data from various sources into Blockwork's own data warehouse. Design and Implement ETL Solutions: You'll be responsible for

About Us: Blockworks is an information platform that sits at the center of the crypto industry. We transform raw, complex data and facts into actionable research, trusted alpha-driven insights, and world-class events. The result is transparency and confidence. Blockworks connects investors and businesses in onchain capital markets. We give businesses a platform to earn trust and provide investors with the information they need to underwrite the asset class. Who You Are: You have a keen focus on backend and API development and Software engineering is your passion. You are a player-coach and a natural leader who understands the technical and human elements that go into great software design. You have a results-oriented attitude and a passion for delivering flawless releases and developing digital product pipelines (CI/CD pipelines). You have a proven track record facilitating engineering teams to increase productivity and quality. You're excited at the possibility of being on the ground floor of the design and development of backend strategies. You bring a passion for designing and maintaining scalable API services that handle large amounts of data elegantly. You love moving quickly in a fast-paced start-up, but you also bring intentionality, sustainability and scalability to your approach as an engineer. What You’ll Do: As a Senior Backend Engineer at Blockworks, you’ll design, build, and maintain the systems that power our products end-to-end. From high-performance APIs to database architecture, you’ll own the backend layer that makes everything else possible. You won’t just be handed requirements, you’ll help define them, scope projects, and make the architectural decisions that shape our technical foundation. Your work will directly impact our research platform ( blockworksresearch.com ) and our media site ( blockworks.co ; 1M+ monthly active users). Every day will look a little different, but in general, you will do things like: Architect, build, and ship backend

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence— you will uncover insights about markets and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a Macro Analyst, Market Intelligence covering the US, you will work with alternative data to gather macroeconomic context and identify insights relevant to rates and FX markets. You will then partner with our team of data scientists and engineers to develop analyses that you deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the markets within your assigned coverage Produce research for internal consumption by our investment professionals across a variety of channels, including written reports, verbal communication, data feeds, and visualizations Interact directly with our investment professionals to learn the macro investment process from them and help drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, evaluate, and draw value from new and existing data assets to produce actionable research for investment professionals WHAT’S REQUIRED &nb