AI Framework Engineer Los Altos, CA · Hybrid

View all jobs AI Framework Engineer Los Altos, CA MAX Hybrid Full-time

About Modular At Modular, a Qualcomm company , 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 this 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 Framework 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: Candidates based in the US are welcome to apply. This role will be based at our Los Altos, CA headquarters (minimum 3 days per week on-site) with relocation assistance provided for out-of-state candidates based in the US. What you will do

• Develop the API surface for MAX: name spaces, 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/Dev Rel 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, Tensor Flow, 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.

What Modular brings to…