Senior AI Framework Engineer United States / Canada · Remote

Modular Inc; Los Altos, Northern (CA, KY); Hybrid; USD 180,000 - 324,000; Full time

Benefits offered by this job

RSU grants

Competitive compensation

Team on-sites in Los Altos

Job summary

Modular Inc. is building a next‑gen AI platform and MAX framework to empower developers with scalable APIs for inference and training. You will shape core APIs, developer experience, and reference implementations while balancing performance, portability and maintainability.

Based in the US/Canada, you can work from our Los Altos, CA office or remotely. Onboarding occurs in person at Los Altos. The role blends API design, systems engineering and modern AI frameworks to ship coherent and powerful

Qualifications

• Significant experience designing and evolving developer-facing APIs (SDKs, frameworks, or platforms).
• Strong understanding of modern AI frameworks and their design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems).
• Experience with inference and training systems (model execution graphs, compilation, runtime scheduling, distributed execution, checkpointing).
• Proficiency in systems languages (C++, Rust, Go) and user languages (Python; Mojo familiarity is a plus).

Responsibilities

• Influence API surface design for MAX: namespaces, core abstractions, extension points, programming model, compatibility guarantees, developer experience.
• Design inference APIs for model loading, distributed inference, quantization, tokenization, batching, and deployment ergonomics.
• Design training APIs for single device to distributed execution with device placement and checkpointing.
• Create coherent Python and Mojo-adjacent surfaces with consistent naming, types, and conventions.

Skills

API design surface

AI framework knowledge

Inference systems

Training systems

Python

C++/Rust/Go

Mojo familiarity

Job description

View all jobs Senior AI Framework Engineer United States / Canada MAX Remote 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 Senior AI Framework Engineer for MAX, you will own and evolve 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 specifications, abstractions, and reference implementations that make MAX feel coherent, powerful, and intuitive to use — while preserving performance, portability, maintainability and TCO. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office.

What you will do

• Influence the design of the API surface for MAX: namespaces, core abstractions, extension points, programming model, compatibility guarantees and developer experience.
• Design inference APIs that support real-world serving needs: model loading, distributed inference, quantization, tokenization/pipelines, configuration surfaces, batching/streaming, and deployment-oriented ergonomics.
• Design training APIs that scale from single device to distributed execution, with clear primitives for device placement, parallelism, checkpointing, and observability.
• Create a coherent programming model across Python and Mojo-adjacent surfaces: align naming, types, and conventions; avoid leaky abstractions; define the \"pit of success\".
• Drive 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.
• Build reference implementations and exemplar code: golden-path examples, architecture templates, and best-practice patterns that teams can copy.
• Set quality bars for APIs: versioning policy, deprecation strategy, test strategy, and documentation requirements.

What you bring to the table

• Significant experience designing and evolving developer-facing APIs (SDKs, frameworks, or platforms).
• Strong understanding of modern AI frameworks and their design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems).
• Experience with inference and training systems (model execution graphs, compilation, runtime scheduling, distributed execution, checkpointing, performance tuning).
• Fluency in one or more systems / performance languages (C++, Rust, Go) and one or more user-facing languages (Python; familiarity with Mojo is a plus).
• Excellent taste for API ergonomics: naming, composability, types, error handling, configurability, and clarity.
• Strong written communication: you can write specs that engineers can implement without ambiguity.
• High engineering standards, pragmatism, and a bias towards incremental development without compromising long term design.

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. Your benefits package may include comprehensive healthcare coverage, retirement and savings programs, employee stock purchase opportunities, paid time off, wellbeing resources, family support programs, and learning and development opportunities. Please note that specific benefit packages may vary based on your location, you can read more about benefits offered by Qualcomm here .
• Competitive Compensation.We offer very strong compensation packages, including RSU grants. 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. 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 share a purpose to fundamentally change how developers build and deploy AI systems. The estimated base salary range for this role to be performed in the US, regardless of the state, is $180,000–$324,000 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $172,400.00–$258,700.00 CAD. 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 total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply, as we may have openings at lower or higher levels than the one advertised.