Ship Suitability Engineer in New York

VP, Product Insurance underwriting runs on human judgment, manual workflows, and knowledge locked in someone's head. It breaks when that person leaves and doesn't scale when the book doubles. Sixfold is building AI agents that understand risk the way a 20-year veteran underwriter does. Not summaries or flags, but systems that make real decisions on billions in premium for some of the world's largest carriers. AI is the product, the workflow, and the moat. If you think in systems, move fluidly from research to pixels, and are energized by designing AI-native experiences where the best practices haven't been written yet — this role was made for you. Who We Are 🏔 Product: Sixfold is the AI brain for underwriting. Our platform handles submissions at scale, assessing risk against appetite, surfacing cited insights, and deploying AI agents to handle research, referrals, and triage so underwriters can focus on building profitable portfolios. 💪 Team: A focused team of insurance operators, AI researchers, and engineers who love hard problems. We've pushed the boundaries of what AI can do with unstructured data — from teaching AI to understand that a bakery in Florida faces different risks than one in Montana, to knowing when a manufacturing company's pivot from toys to medical devices fundamentally changes their risk profile. We ship fast and stay close to customers. 📈 Traction: Processing billions in premium for some of the world's largest carriers. We know AI. We know underwriting. We're building what comes next. About the Role You'll inherit a strong product and a capable team, but that's the starting point, not the job. The job is figuring out what underwriting becomes once AI stops assisting and starts deciding, and getting there faster than the market expects. You prototype to find out, not to perform speed. You're drawn to this problem because the underwriter of the future is one of the more interesting design problems in software right now. In this role, you will:

About the Team The Web team brings OpenAI’s brand, mission, and products to life online. We work across brand design, marketing, communications, and engineering to create clear, accessible web experiences for a global audience. This role is dedicated to Business Marketing, helping organizations understand how OpenAI’s products can support their work. We combine thoughtful storytelling, strong visual craft, and intuitive user experiences to make complex ideas approachable and useful. About the Role We’re looking for a hands-on Web Designer to create exceptional experiences for business audiences on OpenAI.com . You’ll help people understand our products, explore their relevance to their organizations, and find the right next step. As an individual contributor, you’ll own projects from early exploration through launch, working closely with engineers, brand designers, marketers, and writers. You’ll bring strong visual judgment and UX thinking to the work, balancing user needs, business goals, and technical constraints while contributing to a cohesive experience across the site. This role is based in New York, NY. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Own design from concept through implementation, developing information architecture, user flows, wireframes, prototypes, and high-fidelity responsive designs. Translate complex product capabilities and business use cases into clear stories and compelling web experiences. Design product, solution, and campaign experiences that help business audiences discover, evaluate, and take action. Partner with engineers, brand designers, marketers, and writers to shape ideas, make thoughtful tradeoffs, and ship polished work. Evolve and apply our web design system, creating reusable patterns that support both consistency and expressive storytelling. Stay involved through implementation and design QA, paying close attention to accessibil

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 like Anthropic to Fortune 500s like Siemens, Datalab is where businesses turn when extraction has to be right. We hit an 8-figure run rate with a team of 7. We have hundreds of customers across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools - chandra, surya, marker, and lift - have 70,000+ GitHub stars, millions of monthly downloads, and broad developer mindshare. We’re backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview Marketing at Datalab already has real infrastructure behind it. We run a combined launch and content calendar with a defined playbook - channels, owners, and cadence for every release - and we ship two to three launches a week against it. No one here works on marketing full-time, so nobody owns the larger question of how we show up when a developer, a buyer, or an AI agent goes looking for a document parser. You’d be our first dedicated marketing hire. You’d inherit a working system rather than a blank page, and the job is to make it run reliably, then make it considerably more ambitious. The natural place to build from is our open source work, which reaches a wide audience and currently does less for us than it could. This is a hands-on role. On a team of 7, you’ll write the blog post, draft the tweets, restructure the docs page, brief the agency if we hire one, and pull the numbers yourself. We’re looking for someone who has done this work somewhere it was done well, and who wants to keep doing it rather than direct someone else who does. There is strong potential for this to grow into a leadership role as we hire more people into the marketing team. An increasing share of our buyers never touch a search results page; they ask a model. We want someone who t

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-

Salary range: $300k - $350k | Equity: 0.4% - 0.6% | 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 an engineering lead to guide our team while staying hands-on in the code. You'll set the technical direction and standards for how we build the interfaces, tools, and infrastructure behind our OCR, extraction, and document-understanding systems. This includes everything from optimizing agent loops and interfaces to helping to speed up inference. This is a player-coach role. You'll manage and grow a team of three engineers, own engineering delivery and quality, and spend a large share of your time writing code - focused on architecture, infrastructure, and the hard problems rather than routine feature work. You’ll partner closely with the research team to define the handoff between experimentation and production. As a small and fast-moving team, roles are fluid and ownership is high. You'll work directly with the founder to set priorities, ship features, and make our technology accessible to a global community of builders. Day to day, you will: Manage and grow a team of three engineers - 1:1s, prioritization, feedback, and hiring as we scale. Own engineering delivery, quality, and technical standards across code, testing, infrastruct

Founding Engineer, Open Source Salary range — $225k – $300k | Equity — .15%-.35% | 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 Founding Engineer to develop and evangelize our open source repos. This includes chandra, surya, marker, pdftext, and lift, which collectively have over 70k Github stars. It also includes new tools we have yet to build and launch. As you work on our repos, you’ll also become the credible person to evangelize them. You’ll turn your own work into demos, benchmarks, tutorials, and launches. You’ll also support other launches across Datalab, especially when they touch open source components like the SDK. Our projects have real reach: 70k+ GitHub stars and users everywhere from frontier AI labs to Fortune 500s. Your job is to turn that reach into a thriving, engaged developer community through content, code, and showing up where developers already are. If you're the kind of engineer who’s energized by both building things and helping other people build, this is the role for you. Day to day: Own our open source repos and SDK: Drive chandra, surya, marker, lift, and our Python SDK forward as a hands-on contributor. Ship new features and improvements that the market cares about, help plan new versions, and ow

Salary range: $225k - $300k | Equity: 0.15% - 0.35% | 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 fullstack engineer who wants to build the interfaces, tools, and infrastructure that help developers and enterprises use our models. You’ll work across the stack to shape how people interact with OCR, extraction, and document-understanding systems. That includes building core inference workflows, creating intuitive UI for complex parsing tasks, and improving the developer experience across our open-source repos and API. This is a high-ownership role that blends engineering, product thinking, and community engagement. You will work closely with the founders and the rest of the team to ship features, improve performance, and make our technology accessible to a global community of builders. As a small and fast-moving team, roles are fluid. You should enjoy working across backend, frontend, performance, and user-facing surfaces. Your work will directly influence how teams evaluate and deploy our models. Day to day, you will: Ship features to our open source repos, API, and internal tooling. Design and build frontend features that make document parsing more interactive and understandable. Optimize inference performance and improve th

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. I'm hiring a salesperson. Blockworks builds trust in onchain markets. Data, disclosures, investor relations, APIs, ratings, asset monitoring. You'll sell all of it, often in the same proposal, to the largest protocols, institutions, and enterprises entering crypto. Deals run $100K to $500K+, usually with several stakeholders and very little instructions. You'll be a good fit if you: were top of the leaderboard at a tier one sales org believe deals die on Zoom would rather fly to a maybe than email a yes have run a nine-stakeholder deal with no champion have handed a lead to a teammate because they'd win it faster know the difference between pipeline and hope rebuilt a proposal at midnight because procurement moved the goalposts have spent a Friday night on a deal that wasn't yours have flown to the client for a 45-min meeting have sold three complex products in one single contract We need sellers who understand the deal behind the deal, design the path to get there, pull in the right people, and close. The role: full cycle, selling across the entire Blockworks platform. You'll work directly with our Co-Founder and our Head of Commercial. You need to know how to sell into founders and executives. Travel is part of the job. We host conferences in London, Singapore, and New York. We have an office in New York, but big deals don’t close sitting behind a desk. Blockworks is scaling very fast. Our systems are imperfect, our products ship fast, and our map gets redrawn all the time. If you need clean lanes, this will fr

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: We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

Company Description Novo is a venture-backed fintech that simplifies banking for small businesses. Since our Fall 2018 beta launch, we've expanded offerings from free checking accounts and debit cards to lending products, business tools (invoices, bookkeeping, and more), and integrations.Today , Novo is a powerfully simple banking platform that serves over 250,000 small businesses. In addition to providing smart tools built for entrepreneurs to better run and grow their businesses, Novo has processed billions in transactions in partnership with a number of established banking partners. Our vision is to be the go-to platform serving small businesses – from launch to everyday – so business owners can focus on growing, while Novo provides seamless money movement, money storage, and access to capital. We'd like to look back 5–10 years from now and know that we helped new generations of small businesses succeed because of the work we did at Novo. Novo raised $170 million in venture capital and is backed by leading investors, including Stripes, Valar Ventures, Crosslink Capital, and Notable Capital (formerly GGV). Learn more at https://www.novo.co . Role Description Novo is seeking a highly experienced and motivated product manager to own and scale our core banking experience — the accounts, money movement, cards, and program infrastructure that power banking for over 250,000 small businesses. This role is critical to ensuring the reliability, usability, and depth of the products at the heart of Novo, supporting our rapidly expanding customer base and business operations. The ideal candidate is a hands-on product leader who can set product direction for complex, regulated financial products, partner closely with Engineering, Design, Risk, and Compliance, and work hand-in-hand with banking partners to ship reliable, secure, high-quality experiences within a dynamic, regulated fintech environment. Responsibilities Product Strategy & Leadership Own the strategy, roadmap,

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? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. 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, e

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

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, Washington D.C., London and Amsterdam. Plaid’s mission is to unlock financial freedom for everyone by making money movement and access to financial data simple and secure. As a Software Engineer, you will design and build the systems that power how millions of people connect to their finances. You will work across the stack, from reliable backend services and APIs to intuitive applications that bring those systems to life. You will collaborate with engineers, product managers, and designers to ship products that make financial services more accessible and transparent. At Plaid, engineers take ownership early, grow quickly, and see their work reach millions of users. Responsibilities: Design & Development: Build and maintain backend services with a focus on performance, reliability and scalability. Collaboration: Work closely with product managers and other stakeholders to define and implement new features that meet product and customer needs. Code Quality: Write clean, maintainable and efficient code. Testing & Debugging: Develop automated tests to ensure the quality and reliability of the codebase. Troubleshoot and resolve issues. Engage in hands-on coding and architectural design, setting and maintaining high technical standard

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, Washington D.C., London and Amsterdam. The Credit team at Plaid builds lending solutions across the full lender lifecycle — including underwriting, verification, and servicing. We help lenders make faster, more informed decisions using consumer-permissioned financial data. Within Credit, the Insights team develops data-driven products including LendScore, Income Insights, CashFlow Insights, and Network Insights. These products power smarter credit decisioning for lenders of all sizes. As a Product Manager on the Insights team, you will drive execution across our portfolio of credit decisioning products. You’ll work closely with engineering and data science teams to ship high-quality product experiences, and partner with sales and marketing on go-to-market motions. You’ll report to the Insights product lead and play a critical role in ensuring we deliver on our roadmap commitments while maintaining the flexibility to pursue new product opportunities as they emerge. Responsibilities Own end-to-end execution of the product roadmap for LendScore, Income Insights, CashFlow Insights, Network Insights, and new Insights products Write product specs, define requirements, and work with engineering and data science to deliver features on schedule R