AI Library Engineer

Modular
Palo Alto, Seattle
Workplace: RemoteFull timeUSD 167,000 - 185,000 annuallyFunction: Data Science & Machine LearningSkills: ["Communication","API design","Pragmatism","Incremental development","Engineering standards"]

Build and evolve the MAX Framework’s developer-facing APIs for inference and training of AI models. You’ll design core abstractions, extension points, and compatibility guarantees, then implement inference and training surfaces that support distributed execution, quantization, tokenization/pipelines, batching/streaming, and observability. Work across API design, systems engineering, compiler/runtime, kernels, and developer experience to deliver coherent programming models and golden-path reference implementations.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Modular
Modular
3 days ago

AI Library Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Build and evolve the MAX Framework’s developer-facing APIs for inference and training of AI models. You’ll design core abstractions, extension points, and compatibility guarantees, then implement inference and training surfaces that support distributed execution, quantization, tokenization/pipelines, batching/streaming, and observability. Work across API design, systems engineering, compiler/runtime, kernels, and developer experience to deliver coherent programming models and golden-path reference implementations.
Location: Palo Alto, Seattle
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Develop the API surface for MAX, including namespaces, core abstractions, extension points, programming model, compatibility guarantees, and developer experience.
  • •Design inference APIs for real-world serving needs such as model loading, distributed inference, quantization, tokenization/pipelines, configuration surfaces, batching/streaming, and deployment ergonomics.
  • •Develop training APIs that scale from single device to distributed execution, with primitives for device placement, parallelism, checkpointing, and observability.
  • •Create a coherent programming model across Python and Mojo-adjacent surfaces by aligning naming, types, and conventions and defining a clear “pit of success”.
  • •Write and socialize technical RFCs/specs and deliver reference implementations (golden-path examples, templates, and best-practice patterns) with cross-functional partners.
Travel: Low travel

Pay and Benefits

Salary: USD 167,000 - 185,000 annually
Equity and Bonus:Equity
Perks:Health Insurance401kPaid LeaveEquity

Key Requirements

  • •Passion for designing developer-facing APIs (SDKs, frameworks, or platforms).
  • •Good understanding of modern AI frameworks and design tradeoffs (e.g., PyTorch, JAX, TensorFlow, vLLM, XLA/MLIR-adjacent ecosystems).
  • •Proficiency in one or more systems/performance languages (C++, Rust, Go) and user-facing languages (Python; familiarity with Mojo is a plus).
  • •Strong API ergonomics instincts (naming, composability, types, error handling, configurability, clarity).
  • •Write clear technical specs and communicate in a way engineers can implement without ambiguity.
Experience:AI infrastructureDeveloper toolsAI frameworksModel inferenceModel training
Skills:CommunicationAPI designPragmatismIncremental developmentEngineering standards
Tech Stack:MAX FrameworkAPI designPythonMojoC++RustGoPyTorchJAXTensorFlowVLLMXLAMLIRQuantizationTokenizationDistributed inferenceBatchingStreamingObservabilityRFCs

Company Brief

Modular
Provides infrastructure and developer tools to build, deploy, and scale large AI models and foundation-model applications, including model hosting, orchestration, and SDKs to accelerate AI product development.
Industry: AI & Machine Learning
Website