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Machine Learning Compiler Engineer

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Machine Learning Compiler Engineer in USA new

  • Jane Street
  • Full time
  • Email
  • New York, NY

Responsibilities

  • Shape the development of Jane Street’s ML compiler stack.
  • Improve compiler technologies to support high-throughput training and low-latency inference.
  • Work on compiler optimization, graph capture, symbolic and dynamic shapes, control flow, and automatic differentiation.
  • Develop or optimize GPU kernels and leverage GPU architectures, tensor cores, and compute and memory hierarchies.
  • Support ML inference and training systems, including batching, caching, parallelism, checkpointing, and communication.
  • Investigate compiler concepts, formal methods, programming languages, and domain-specific language design.

Requirements

  • Experience working on an ML compiler is ideal, while non-ML compiler experience is also valuable.
  • Understanding of ML compiler stacks, including high-level frameworks, graph compilers, and kernel DSLs.
  • Interest or experience in algebraic rewriting, fusion, scheduling, loop-level optimization, autotuning, or related compiler optimizations.
  • Knowledge of compiler concepts such as static analysis, intermediate representations, instruction selection, SSA, or CFGs.
  • Experience or interest in GPU kernel programming, CUDA, tensor cores, GPU debugging, and performance optimization.
  • Familiarity with ML inference, ML training parallelism, formal methods, programming languages, or DSL design is valuable.

Jane Street

Jane Street is a quantitative trading firm with offices in New York, London, Hong Kong, Singapore, and Amsterdam. We are always recruiting top candidates and we invest heavily in teaching and training. The environment at Jane Street is open, informal, intellectual, and fun. People grow into long ...

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