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Freelance Machine Learning Compiler Engineer Jobs in Texas

Nvidia

Senior AI Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to join our team. The ideal candidate will bring broad experience across the machine learning ...

Nvidia

Senior Deep Learning Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling ...

Nvidia

Senior ML Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

Innovate and develop new machine learning compiler and systems technologies * Design, implement ... Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for ...

NVIDIA

Senior Compiler Engineer - AI

Austin, TX · On-site

$103K - $142K/yr

The role involves driving innovative solutions in compilers and developer tools through applied machine learning and AI, focusing on building AI-driven compiler intelligence for production pipelines.

Nvidia

Senior Compiler Engineer - Backend

Austin, TX

Our Compiler team is responsible for constructing and emitting the highest performance GPU machine ... Be part of a team that is at the center of deep-learning compiler technology spanning architecture ...

Nvidia Corporation

Senior Compiler Engineer - AI

Austin, TX · On-site

$121K - $160K/yr

We are seeking an AI Compiler Engineer with deep expertise in compiler technologies to join our ... The ideal candidate brings broad experience across machine learning, including reinforcement ...

Nvidia

Senior Compiler Engineer - AI

Austin, TX

$121K - $160K/yr

We are seeking an AI Compiler Engineer with deep expertise in compiler technologies to join our ... The ideal candidate brings broad experience across machine learning, including reinforcement ...

Nvidia

Senior Compiler Engineer - DL

Austin, TX

$121K - $160K/yr

NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling ...

Tenstorrent

GCC Compiler Engineer

Austin, TX · On-site

$100K - $500K/yr

We are seeking a GCC Compiler Engineer to design, develop, and optimize compilers for next ... machine learning workloads. This role isHybrid, based out of Santa Clara, CA, Austin, TX, or ...

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Freelance Machine Learning Compiler Engineer information

What is the difference between Freelance Machine Learning Compiler Engineer vs Freelance Software Developer?

AspectFreelance Machine Learning Compiler EngineerFreelance Software Developer
Required SkillsMachine learning frameworks, compiler optimization, programming (C++, Python)General programming, software design, various languages
Work EnvironmentProject-based, remote, often technical teams in AI/ML industryVaried industries, remote or on-site, broad application areas
Industry UsageAI/ML companies, research labs, tech firmsTech, finance, healthcare, startups, enterprise

Freelance Machine Learning Compiler Engineers focus on optimizing ML models for deployment, requiring specialized knowledge in ML frameworks and compiler technology. Freelance Software Developers have broader roles across various industries, working on diverse software projects. Both roles are in high demand but differ in technical focus and industry application.

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Freelance Machine Learning Compiler Engineer jobs near you
Compiler Engineer - Machine Learning Compiler

Compiler Engineer - Machine Learning Compiler

Mythic

Austin, TX • On-site

Full-time

Posted 4 days ago

Job description

About us

Mythic is building the future of AI computing with breakthrough analog technology that delivers 100 the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 C to +125 C, making it ideal for industrial, automotive, aerospace, and defense.
We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

About the role

Join us in building the next generation of AI compilers. You'll play a key role in developing the compiler for our novel AI accelerator, working side-by-side with hardware engineers and ML researchers. Your work will shape how deep learning workloads run on cutting-edge dataflow hardware-defining the instruction set, execution model, and developer experience. The result: a compiler that delivers breakthrough performance while remaining seamless and intuitive for ML developers.
Here's what you will do
  • Contribute across the full compiler stack, including operator lowering, graph/IR transformations, optimization passes, and backend code generation
  • Optimize for dataflow architectures, developing pipelined schedules, memory orchestration, and resource-constrained execution strategies
  • Collaborate with hardware architects to influence architectural features, ensuring the compiler and hardware evolve together
  • Develop compilation strategies that unify our analog compute with digital subsystems
  • Build and maintain a compiler that produces high-performance binaries with strong debugging support, clear error messages, and predictable performance models
Here's the background we hope you will have
  • 3+ years of experience building compilers or high-performance systems software, especially those involving complex resource management or optimization.
  • Expert in modern C++ (C++14/17/20) and strong Python.
  • Experience with compiler IRs (SSA-based or graph-based), transformations, and code generation
  • Exposure to specialized accelerators (GPU, NPU, FPGA, or custom ASIC) or parallel architectures
The following would be nice to have, but is not required
  • Experience with machine learning compiler stacks (e.g., ONNX, MLIR, TVM, XLA, IREE, PyTorch), with contributions to MLIR or LLVM projects a plus
  • Experience with optimization methods (LP/MIP, CP, SAT/SMT) using solvers like Gurobi or OR-Tools for scheduling and resource allocation
  • Experience compiling for specialized accelerators (GPU, NPU, FPGA, or custom ASIC) on DNN workloads; GPU/DSP experience is valuable if combined with compiler backend work beyond kernel tuning
  • Familiarity with heterogeneous compilation, especially mixing custom accelerators with CPUs/GPUs/NPUs, and exposure to analog or in-memory compute is a plus
  • Experience collaborating in compiler-hardware co-design (architecture + ISA) for better compiler usability and hardware efficiency
What we offer
  • The opportunity to shape how deep learning and LLM workloads are compiled on novel hardware.
  • A role that spans software and hardware co-design, shaping both the compiler and the accelerator architecture
  • A collaborative, innovative team that values engineering rigor, continuous integration, and user-focused design. We foster an environment of shared learning and technical excellence
  • Competitive compensation, equity, and benefits package
At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.
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