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Machine Learning Software Engineer Jobs in Seattle, WA

Nvidia

Senior Deep Learning Software Engineer

Redmond, WA · Hybrid

$137K - $180K/yr

This is an exceptional opportunity for passionate software engineers straddling the boundaries of research and engineering, with a strong background in both machine learning fundamentals and software ...

Emonics LLC

Machine Learning Engineer

Seattle, WA · On-site

You will work with data scientists and software engineers to create scalable ML solutions ... machine learning pipelines Requirements Knowledge of Python and machine learning algorithms ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Collaborate with data scientists and flight software engineers to integrate AI capabilities into ... Proven experience deploying machine learning models into production. * Strong software engineering ...

New

Apple

Machine Learning Engineer

Seattle, WA

$171K - $302K/yr

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... Minimum Qualifications Software engineering skills and proficiency in Python Experience with ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

If you also have knowledge of data science and software engineering, we'd like to meet you. Your ... Design machine learning systems * Research and implement appropriate ML algorithms and tools

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

If you also have knowledge of data science and software engineering, we'd like to meet you. Your ... Design machine learning systems * Research and implement appropriate ML algorithms and tools

Overland AI

Software Engineer, Machine Learning

Seattle, WA · On-site

$120K - $300K/yr

The company leverages over a decade of advanced research in robotics and machine learning, as well as a field-test forward ethos, to deliver combined capabilities for unit commanders. Our OverDrive ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Experience in software engineering with a focus on distributed systems and scalable backend ...

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Machine Learning Software Engineer information

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$72.3K

$167.9K

$233.9K

How much do machine learning software engineer jobs pay per year?

As of Jul 2, 2026, the average yearly pay for machine learning software engineer in Seattle, WA is $167,886.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,600.00 and $196,900.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

What are the key skills and qualifications needed to thrive in the Machine Learning Software Engineer position, and why are they important?

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.

What are popular job titles related to Machine Learning Software Engineer jobs in Seattle, WA? For Machine Learning Software Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Software Engineer jobs in Seattle, WA look for? The top searched job categories for Machine Learning Software Engineer jobs in Seattle, WA are:
Machine Learning Software Engineer jobs near you
Senior Deep Learning Software Engineer

Senior Deep Learning Software Engineer

Nvidia

Redmond, WA • Hybrid

$137K - $180K/yr

Full-time

Posted 2 days ago

Job description

We are looking for a Senior Deep Learning Software Engineer to design and build our automated inference and deployment solution. As part of the team, you will be instrumental in defining a scalable architecture for DL inference with emphasis on ease-of-use and compute efficiency. Your work will span multiple layers of the DL deployment stack, encompassing developing features in high-level frameworks like PyTorch and JAX, designing and implementing a high-performance execution environment, low-level GPU optimizations and developing custom GPU kernels in CUDA and/or Triton. This is an exceptional opportunity for passionate software engineers straddling the boundaries of research and engineering, with a strong background in both machine learning fundamentals and software architecture & engineering.

What you'll be doing:

  • Play a pivotal role in defining of a modular, scalable platform to seamlessly bridge training and deployment workflows-enabling tight integration of deployment tooling with training frameworks such as Megatron and Nemo

  • Leverage and build upon the torch 2.0 ecosystem (TorchDynamo, torch.export, torch.compile, etc...) to analyze and extract standardized model graph representation from arbitrary torch models for our automated deployment solution.

  • Develop support for inference optimization techniques such as speculative decoding and LoRA.

  • Collaborate with teams across NVIDIA to use performant kernel implementations within the automated deployment solution.

  • Analyze and profile GPU kernel-level performance to identify hardware and software optimization opportunities.

  • Continuously innovate on the inference performance to ensure NVIDIA's inference software solutions (TRT, TRT-LLM, TRT Model Optimizer) can maintain and increase its leadership in the market.

What we need to see:

  • Masters, PhD, or equivalent experience in Computer Science, AI, Applied Math, or related field.

  • 8+ years of relevant work or research experience in Deep Learning.

  • Excellent software design skills, including debugging, performance analysis, and test design.

  • Strong proficiency in Python, PyTorch, and related ML tools.

  • Strong algorithms and programming fundamentals.

  • Good written and verbal communication skills and the ability to work independently and collaboratively in a fast-paced environment.

Ways to stand out from the crowd:

  • Contributions to PyTorch, JAX, or other Machine Learning Frameworks.

  • Knowledge of GPU architecture and compilation stack, and capability of understanding and debugging end-to-end performance.

  • Familiarity with NVIDIA's deep learning SDKs such as TensorRT.

  • Prior experience in writing high-performance GPU kernels for machine learning workloads in frameworks such as CUDA, CUTLASS, or Triton.

Increasingly known as "the AI computing company" and widely considered to be one of the technology world's most desirable employers. Are you creative, motivated, and love a challenge? If so, we want to hear from you! Come, join our model optimization group, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly-growing field.

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 28, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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