VP of Engineering

Location: Brooklyn, NY or Bay Area preferred

Mathpix is looking for a VP of Engineering to lead our growing engineering organization. You'll own the technical roadmap, drive execution across backend, infrastructure, and ML teams, and ensure we ship reliable, scalable systems that power our document conversion products. This is a hands-on leadership role — you'll set the bar for engineering quality while building the team and processes needed to scale.

The ideal candidate has led engineering teams at high-growth startups, has deep experience with distributed systems and ML infrastructure, and thrives in environments where they can both architect solutions and mentor engineers.

Responsibilities:

• Lead and grow the engineering team, including hiring, mentoring, and setting technical direction
• Own the engineering roadmap and ensure alignment with business objectives
• Drive architectural decisions across backend services, infrastructure, and ML systems
• Establish and refine engineering processes for reliability, velocity, and quality
• Partner with ML leadership to ensure models are deployed and scaled effectively in production
• Oversee incident response, production health, and operational excellence

Required skills:

• 7+ years of software engineering experience, with 3+ years in engineering leadership
• Experience scaling engineering teams and systems at high-growth companies
• Deep technical expertise in distributed systems, cloud infrastructure (AWS), and container orchestration (Kubernetes)
• Strong background in Python and/or Go for backend systems
• Track record of shipping and operating mission-critical production systems
• Excellent communication skills and ability to work closely with founders and cross-functional teams

Nice to have:

• Experience with ML infrastructure and model deployment pipelines
• Familiarity with computer vision, OCR, or document processing systems
• Experience building developer tools and improving engineering productivity
• Experience at a startup or high-growth company; founding/early-team experience is a bonus
• Contributions outside of work — personal projects, open-source, articles, or blog posts

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Senior Machine Learning Engineer

Location: Brooklyn, NY or Bay Area preferred

Mathpix is looking for a Senior Machine Learning Engineer with deep expertise in computer vision, sequence modeling, and multimodal AI. As a leader on our ML team, you'll play a pivotal role in advancing the state of the art in OCR and related applications, building custom models that push the boundaries of what's possible in text recognition, document understanding, and multimodal learning.

The ideal candidate has a PhD in CS, ML, CV, NLP, or a related field, and many years of experience designing, training, and deploying deep learning models at scale. They have worked on sequence-to-sequence models, attention mechanisms, and large multimodal systems, and are motivated by the challenge of building production-grade AI models for mission-critical applications.

Responsibilities:

• Research, design, and implement custom deep learning models for OCR and multimodal document understanding tasks
• Build and train sequence-to-sequence and attention-based architectures for text recognition, translation, and generation tasks
• Lead development of multimodal language models that combine vision and text for real-world applications (e.g., image-to-text, document parsing)
• Optimize and extend PyTorch-based training pipelines for large-scale datasets and high-performance inference
• Collaborate with product and engineering teams to integrate models into production systems, ensuring scalability, robustness, and efficiency
• Work closely with the in-house data team to define, generate, and curate high-quality training data, enabling rapid iteration on bug fixes and the development of new features
• Mentor junior engineers and provide technical leadership in model architecture, experimentation, and deployment best practices

Required skills:

• PhD in Computer Science, Machine Learning, Computer Vision, NLP, or a related field
• 3+ years of hands-on experience in deep learning research and development
• Strong expertise in sequence-to-sequence models, attention mechanisms, and Transformer-based architectures
• Proven experience building and training custom models in PyTorch (not using off-the-shelf models)
• Track record of work in one or more of the following areas: machine translation, text generation, speech-to-text, OCR, image captioning, or related multimodal tasks
• Deep understanding of core ML concepts: optimization, regularization, model scaling, and distributed training
• Demonstrated ability to take models from research to production in a high-stakes environment

Nice to have:

• Experience with large-scale multimodal foundation models and techniques for fine-tuning/adaptation
• Knowledge of advanced evaluation methodologies for sequence and multimodal models
• Publications in top ML/AI/vision conferences or journals (e.g., NeurIPS, CVPR, ACL, ICML)
• Experience mentoring teams and driving research agendas in applied AI settings
• Experience at a startup or high-growth company; founding/early-team experience is a bonus
• Contributions outside of work — personal projects, open-source, articles, or blog posts

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Research Engineer / Applied Scientist

Location: Brooklyn, NY or Bay Area preferred

Mathpix is looking for a Research Engineer / Applied Scientist to join our team. We believe the hardest part of being a great applied scientist isn't knowing the latest model architectures — it's being able to design and run long-horizon computational experiments, debug from first principles, and teach yourself whatever you need to know to make progress on a hard problem. Those are exactly the skills a strong PhD already has. We'd rather hire that mindset and bring you up to speed on modern ML and computer vision than hire the marginal ML PhD.

We're especially interested in PhDs from physics, applied math, computational chemistry, astronomy, computational biology, neuroscience, electrical engineering, mechanical engineering, and adjacent quantitative disciplines. If you spent years running simulations on a cluster, writing performance-critical Python or C++ on Linux, and self-teaching whatever technique your thesis required — we want to talk to you, whether or not you've done ML before. You'll work on real problems in document understanding alongside our ML and engineering teams, with room to grow into whichever parts of the stack you find most interesting.

Responsibilities:

• Design and run large-scale computational experiments to evaluate and improve our ML systems and document processing pipelines
• Implement performance-critical components in Python and/or C++ on Linux
• Investigate model failure modes and pipeline edge cases from first principles, using whatever tools the problem requires
• Pick up unfamiliar techniques — new model architectures, optimization methods, evaluation methodologies — and apply them to production problems
• Collaborate with the ML team on data curation, training, and evaluation, and with engineering on integrating results into production

Required skills:

• PhD in physics or another quantitative discipline (applied math, computational chemistry, astronomy, computational biology, EE, ME, etc.), or equivalent research experience
• Strong programming skills on Linux in Python and/or C++
• Track record managing a multi-month computational research project end-to-end — designing experiments, running them, debugging, iterating, drawing conclusions
• Demonstrated ability to self-teach difficult technical material

Nice to have:

• Exposure to deep learning, especially in PyTorch
• Experience with HPC clusters, GPUs, or distributed compute
• Publications in your field
• Background in OCR, computer vision, NLP, or document understanding
• Open-source contributions, technical writing, or other work shared publicly

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Senior Backend Engineer

Location: Brooklyn, NY or Bay Area preferred

Mathpix is looking for a Senior Backend Engineer passionate about building robust, scalable distributed systems that power mission-critical applications. This role involves working across multiple layers of the stack, from databases and message queues to container orchestration and observability systems. You'll play a key role in shaping how our engineering teams build, scale, and operate services that need to perform reliably under real-world load.

The ideal candidate is excited about tackling complex technical challenges, designing resilient architectures, and improving developer productivity through better tooling and infrastructure.

Responsibilities:

• Design and build distributed systems with a focus on scalability, resilience, and maintainability
• Develop tools for observability and monitoring, enabling teams to quickly detect, diagnose, and resolve issues
• Architect and optimize data-intensive systems, ensuring high availability, performance, and consistency
• Enhance developer productivity by improving CI/CD pipelines, containerization, and infrastructure-as-code

Required skills:

• 5+ years of experience with distributed systems, message queues, and observability pipelines
• Strong experience with SQL databases
• Expertise in Kubernetes (K8s) and Docker
• Experience building and maintaining microservices in production, including service-to-service communication and API design
• Hands-on experience with Redis for caching and fast data access
• Knowledge of message queues (e.g., RabbitMQ) for distributed event-driven architectures

Nice to have:

• Proficiency in Python, Node.js, Java, and/or Golang for building and maintaining APIs and services
• Experience with cloud platforms (AWS, GCP, or Azure)
• Familiarity with observability tooling (e.g., OpenTelemetry, Prometheus, Grafana)
• Experience at a startup or high-growth company; founding/early-team experience is a bonus
• Contributions outside of work — personal projects, open-source, articles, or blog posts

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Full Stack Engineer — Internal Tools & Web

Location: Brooklyn, NY or remote

Mathpix is looking for a Full Stack Engineer to own the internal tools and web surfaces our team and customers rely on every day. This is high-leverage work. You'll own Zenpix, the internal platform where our annotation and ML teams direct, review, and measure the data that trains our models, and you'll build on console-web, the app our cloud customers use to manage their accounts. The quality of these surfaces shapes both how fast our researchers move and how our customers experience the product — so the person in this seat frees up some of our most senior people to focus on the hardest problems.

We care more about how you think than what's on your resume, but this is a role for someone who has already shipped real web applications and is ready to own meaningful surfaces with minimal direction. You'll work across a React/TypeScript and Python/PostgreSQL stack, collaborate closely with ML researchers and the data team, and take projects from design through deployment.

Responsibilities:

• Own features in Zenpix — our internal annotation editors, dashboards, and data tooling (React/TypeScript + Python/Flask, PostgreSQL) — the high-leverage platform our data and ML teams depend on
• Build and improve console-web, the web app cloud customers use to manage API keys, usage, and billing
• Own data-team tooling: annotation queue creation, synthetic-data generation, and validation dashboards that keep our training-data pipeline moving
• Run QA across our Snip apps and web surfaces for release, so release readiness doesn't rest on a single person
• Take projects end-to-end, from design through deployment and monitoring, and partner with ML researchers so their time goes to models, not tooling

Required skills:

• A few years building and shipping full-stack web applications
• Strong with React/TypeScript on the front end and Python on the back end
• Comfortable with SQL and relational databases (PostgreSQL)
• A self-starter who owns outcomes end-to-end and collaborates well
• Genuine care for the quality and usability of tools other people depend on

Nice to have:

• Experience building internal tools, dashboards, or data-annotation/labeling interfaces
• Exposure to ML workflows or PyTorch (you'll work alongside our research team)
• QA / release-testing experience for web or desktop apps
• Familiarity with Flask, WebSockets, or Docker
• Contributions outside of work — personal projects, open-source, articles, or blog posts