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Freelance Machine Learning Compiler Engineer Jobs in Washington

AI Compiler Engineer U.S., Canada, Germany, Norway, India EnCharge AI is a leader in advanced AI ... Implement parsing, semantic analysis, and IR generation for deep learning frameworks. * Research ...

Machine Learning Engineer Role Summary: The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main ...

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

Machine Learning Engineer D.C. Area About the Position As a member of our Engineering team, you will work with a tight, highly skilled machine learning / data science team dedicated to the ...

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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.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Washington? The most popular types of Machine Learning Compiler Engineer jobs in Washington are:
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What cities in Washington are hiring for Freelance Machine Learning Compiler Engineer jobs? Cities in Washington with the most Freelance Machine Learning Compiler Engineer job openings:

AI Compiler Engineer

EnCharge AI

Washington, DC • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

AI Compiler Engineer

U.S., Canada, Germany, Norway, India

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge's robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today's best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems.

About the Role

EnCharge AI is seeking a highly skilled and experienced AI Compiler Engineer to spearhead the efforts in developing and optimizing graph compilers tailored to cutting-edge AI and ML workloads. You will collaborate with hardware architects, and AI researchers to enhance performance, optimize computation graphs, and enable efficient model deployment on EnCharge's Inference Accelerators.

Responsibilities
  • Architect, design, and implement optimizations for AI model execution on graph compilers to improve performance, reduce latency, and maximize hardware utilization.
  • Work closely with ML researchers, hardware engineers, and software developers to design and deploy AI models, understanding and addressing hardware-specific challenges.
  • Work on performance optimizations for neural network models, such as layer fusion, operator fusion, and graph-level transformations.
  • Develop compiler optimizations and passes that convert high-level AI models (e.g., from TensorFlow, PyTorch) into intermediate representations (IR).
  • Implement parsing, semantic analysis, and IR generation for deep learning frameworks.
  • Research and integrate the latest advancements in compiler design, ML model optimizations, and hardware acceleration into graph compilers.
  • Provide leadership, mentorship, and technical guidance to a team of engineers focused on graph compiler optimizations.
Qualifications
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field (Ph.D. preferred).
  • 3+ years in compiler development, with a strong focus on AI or ML graph compilers.
  • Proficiency in AI graph compiler frameworks (e.g., MLIR, Torch-FX)
  • Solid background in hardware architectures (e.g., GPUs, TPUs, ASICs) and optimization techniques such as fusion, quantization, and tiling.
  • Familiarity with neural networks operators and code generation.
  • Strong understanding of intermediate representations, code parsing, and semantic analysis in compiler design.
  • Proficiency in C++, Python, or other programming languages commonly used in compiler development.
  • Open-source contributions to AI software frameworks and libraries is a plus
  • Demonstrated experience leading and mentoring engineering teams with successful project delivery.

EnchargeAI is an equal employment opportunity employer in the United States.