AI Library Engineer in Palo Alto, California at Modular

About Modular
At Modular, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about our culture and careers to understand how we work and what we value.

About the role:At Modular, we are building a next generation AI platform to power modern applications and facilitate access to cutting-edge hardware. The MAX Framework is our developer-facing layer: it defines the APIs developers use to express models, integrate custom kernels, orchestrate execution, iterate on quality and ship systems into production.As an AI Library Engineer for MAX, you will work with core APIs and developer experience for inference and training of AI models. You will work at the intersection of API design, systems engineering, and modern AI frameworks. Your output will be the implementations that make MAX feel coherent, powerful, and intuitive to use — while preserving performance, portability, maintainability and TCO.
LOCATION: North America (Palo Alto / Seattle / remote), or as aligned with the team.
What you will do:

• Develop the API surface for MAX: namespaces, core abstractions, extension points, programming model, compatibility guarantees and developer experience.
• Develop and design inference APIs that support real-world serving needs: model loading, distributed inference, quantization, tokenization/pipelines, configuration surfaces, batching/streaming, and deployment-oriented ergonomics.
• Develop training APIs that scale from single device to distributed execution, with clear primitives for device placement, parallelism, checkpointing, and observability.
• Contribute to a coherent programming model across Python and Mojo-adjacent surfaces: align naming, types, and conventions; avoid leaky abstractions; define the "pit of success".
• Work on technical RFCs and technical specs: write and socialize proposals; gather feedback from internal model engineers and external users; iterate towards consensus.
• Partner cross-functionally with compiler/runtime, kernels, cloud/serving, and documentation/DevRel teams to ensure APIs map cleanly to underlying capabilities.
• Develop reference implementations and exemplar code: golden-path examples, architecture templates, and best-practice patterns that teams can copy.

What you bring to the table:

• Passion for designing developer-facing APIs (SDKs, frameworks, or platforms).
• Good understanding of modern AI frameworks and their design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems).
• Proficiency in one or more systems / performance languages (C++, Rust, Go) and one or more user-facing languages (Python; familiarity with Mojo is a plus).
• Good instincts and a passion for API ergonomics: naming, composability, types, error handling, configurability, and clarity.
• Strong written communication: you can write specs that engineers can implement without ambiguity.
• Passion for engineering standards, pragmatism, and a bias towards incremental development without compromising long term design.

Nice to have

• Prior experience in an AI framework or library.
• Prior experience in developer experience research.
• Prior experience designing programming languages and abstractions

What success looks like (first 3–6 months)

• Direct contribution to various API surfaces, grounded in concrete developer journeys.
• One or more high-impact developments (e.g., a simplified public namespace, clarified tiers such as low-level vs high-level APIs, improved config surfaces).
• Reference examples and docs that unblock internal model bring-up and external adoption

What Modular brings to the table:

• Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
• World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location.
• Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.
• Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles.

Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $167,000 - $185,000 USD.
The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation.For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.