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Remote Machine Learning Compiler Engineer Jobs (NOW HIRING)

Baidu USA

Software Engineer - Compiler

Sunnyvale, CA · On-site +1

Description We are looking for general or deep learning compiler engineers to join our compiler ... Partially remote working is acceptable for this position. We are building a new team of exceptional ...

Nvidia

Senior Compiler Engineer Infrastructure

OR · On-site +1

$108.40K - $147.40K/yr

We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler ... Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With ...

Nvidia

Senior Compiler Engineer Infrastructure

Redmond, WA · On-site +1

$121.50K - $165.20K/yr

We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler ... Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With ...

Nvidia

Senior Compiler Engineer Infrastructure

Austin, TX · On-site +1

$107.50K - $146.20K/yr

We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler ... Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With ...

Nvidia

Senior Compiler Engineer Infrastructure

Santa Clara, CA · On-site +1

$127.40K - $173.20K/yr

We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler ... Familiarity with deep learning frameworks and performance-sensitive workloads on NVIDIA GPUs With ...

Ventana Micro Systems

Compiler Engineer

Cupertino, CA · On-site +1

$105K - $260K/yr

San Francisco Bay Area, Cupertino, or Fully Remote Position: Compiler Engineer Status: Full time with immediate start Qualifications Required: * 12+ years of software development and debugging with C ...

Lemurian Labs

Senior DSL Engineer

Santa Clara, CA · On-site +1

$143.90K - $189.70K/yr

About the Role We are building a domain-specific language and compiler toolchain for programming machine learning models. As a Senior DSL Compiler Engineer, you will focus on the compiler frontend ...

ManTech International

Machine Learning Engineer

$128.80K - $214.50K/yr

General information Requisition # R67616 Locations USA-Remote Work Posting Date 05/19/2026 Security ... The Machine Learning Engineer will leverage their strong technical background and knowledge to ...

Ventana Micro Systems

Compiler Engineer

$105K - $225K/yr

San Francisco Bay Area, Cupertino, or Fully Remote Position: Full time with immediate start ... Strong background in compiler theory, algorithms, and optimization techniques * Hands-on ...

Pluralsight LLC

Machine Learning Engineer

$121.60K - $160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests ... This is a remote role; however, applicants located within 45 miles of our Westlake/Dallas, TX ...

Qwiet AI

Senior Software Engineer (Remote)

$125.40K - $165.30K/yr

... machine learning engineers, security researchers, software engineers, etc. Responsibilities ... Translate source code compiler/parser representation into Joern Code Property Graphs * Keep track ...

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All JobsRemote Machine Learning Compiler Engineer Jobs

Remote Machine Learning Compiler Engineer information

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$75K

$167.4K

$205K

How much do remote machine learning compiler engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for remote machine learning compiler engineer in the United States is $167,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $143,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Compiler Engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

More about Remote Machine Learning Compiler Engineer jobs
What cities are hiring for Remote Machine Learning Compiler Engineer jobs? Cities with the most Remote Machine Learning Compiler Engineer job openings:
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Remote Machine Learning Compiler Engineer jobs near you
Infographic showing various Remote Machine Learning Compiler Engineer job openings in the United States as of May 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 100% Remote job distribution, with an average salary of $167,438 per year, or $80.5 per hour.
Compiler Engineer - Machine Learning Compiler

Compiler Engineer - Machine Learning Compiler

Mythic

Palo Alto, CA • Remote

Full-time

Posted 22 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.