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Full Time Machine Learning Compiler Engineer Jobs

Senior Deep Learning Compiler Engineer

Redmond, WA ยท On-site

$117K - $160K/yr

They are seeking a Deep Learning Compiler Engineer to analyze deep learning networks and develop compiler optimization algorithms, collaborating with various teams to enhance deep learning software ...

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 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 ...

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 ...

New

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 ...

New

Senior Compiler Engineer - AI

Redmond, WA ยท On-site

$117K - $160K/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.

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Full Time Machine Learning Compiler Engineer information

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$31.5K

$128.8K

$193.5K

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

As of Jul 16, 2026, the average yearly pay for full time machine learning compiler engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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

AspectFull Time Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong programming and analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization and ML infrastructureData analysis teams, focusing on data modeling, visualization, and insights
Industry UsageTech companies, AI startups, hardware firmsFinance, healthcare, marketing, and tech sectors

The Full Time Machine Learning Compiler Engineer primarily develops and optimizes compilers for ML models, requiring deep technical knowledge of compiler architecture. In contrast, Data Scientists analyze data to generate insights and build models without focusing on compiler development. Both roles are essential in AI-driven industries but serve different technical and business functions.

More about Full Time Machine Learning Compiler Engineer jobs
What are the most commonly searched types of Machine Learning Compiler Engineer jobs? The most popular types of Machine Learning Compiler Engineer jobs are:

Machine Learning Compiler Architect

Futran Tech Solutions Pvt. Ltd.

Mountain View, CA โ€ข On-site

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Job Title : Machine Learning Compiler Architect
Location : Mountain View, CA(Hybrid)
Responsibilities
Compiler Architecture & Design
Design and develop a robust compiler architecture that effectively interacts with our NPU
Implement advanced graph optimizations that incorporate both hardware agnostic and hardware specific enhancements
Develop and optimize algorithms for tiling and memory management to efficiently utilize the NPU's resources
Create sophisticated optimization passes for neural network inference and training workloads
Code Generation & Hardware Integration
Map high-level operations to optimized library macros and convert them into hardware-level instructions
Generate and manage DMA commands to facilitate data movement and operation within the hardware ecosystem
Collaborate with hardware engineers and system architects to ensure seamless integration and maximal performance of the NPU
Implement efficient scheduling and resource allocation algorithms for concurrent AI workload execution
Innovation & Technology Leadership
Stay updated with the latest trends and advancements in compiler technology and machine learning to continuously improve the compiler design
Lead research initiatives in advanced compilation techniques for AI accelerators
Drive adoption of cutting-edge optimization strategies and compilation methodologies
Mentor engineering teams on compiler design principles and best practices
Skills
Must have
General Skills:
Expert communicator across cultural and team boundaries
Expertise in motivating teams and fostering a collaborative and productive environment
Background in managing multiple and competing stakeholder interests; establishing trust, clear roles and responsibilities, and goodwill between partner engineering organizations
Experience managing cross-functional and/or cross-team projects
Technical leadership experience with ability to mentor engineering teams
Strategic thinking capabilities with focus on long-term architectural decisions
Collaborate and work with multiple teams across geographies and time zones
Required Specialized Skills:
12+ years of experience in compiler development or architecture, particularly targeting AI or ML hardware accelerators
Strong understanding of machine learning algorithms and their computational implications
Working experience with TVM, IREE, XLA, MLIR or LLVM
Proficiency in programming languages such as C++ and Python
Experience with graph optimization techniques and memory management strategies in compilers
Demonstrated ability to translate high-level functional requirements into detailed technical designs
Deep knowledge of hardware architecture principles and AI accelerator design concepts
Proven track record of leading compiler architecture projects from concept to production deployment