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Senior Machine Learning Engineer Jobs in Kent, WA

Axon

Senior Machine Learning Engineer II

Seattle, WA · Hybrid

$139.40K - $183.80K/yr

... new machine learning models and AI capabilities, leading to better and more responsible AI ... Senior Director, AI Platform Engineering Direct Reports: * Architect and develop secure, privacy ...

Expedia

Senior Machine Learning Scientist

Seattle, WA · On-site +1

$104.10K - $142.30K/yr

Senior Machine Learning Scientist The Senior Machine Learning Scientist is responsible for building ... Partners closely with product, engineering, and operations while mentoring junior scientists and ...

Uber

Sr Machine Learning Engineer, Pricing

Seattle, WA · On-site +1

... senior engineers within the organization, setting you up for fast-tracked career growth and the ... S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or ...

Axon

Senior Machine Learning Engineer II

Seattle, WA · On-site

... new machine learning models and AI capabilities, leading to better and more responsible AI ... Senior Director, AI Platform Engineering Direct Reports: * Architect and develop secure, privacy ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

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Senior Machine Learning Engineer information

See Kent, WA salary details

$67.2K

$142.9K

$207.2K

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

As of May 29, 2026, the average yearly pay for senior machine learning engineer in Kent, WA is $142,869.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $162,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Kent, WA? The most popular types of Machine Learning Engineer jobs in Kent, WA are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Kent, WA? For Senior Machine Learning Engineer jobs in Kent, WA, the most frequently searched job titles are:
What cities near Kent, WA are hiring for Senior Machine Learning Engineer jobs? Cities near Kent, WA with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Senior Machine Learning Engineer (Temporary)

Senior Machine Learning Engineer (Temporary)

Brooks Running

Seattle, WA

$69.76 - $111.61/hr

Temporary

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago

Job description

Who We Are:

At Brooks, we believe movement is the key to feeling more alive. That's why we're driven to create gear and experiences that take people to the place that makes them feel more alive - whether it's a headspace, a feeling, or a finish line. 

Everyone who works at Brooks is propelled by a company culture that sparks excitement, fuels collaboration, inspires creativity, and ignites innovation.

Our brand values help bond us together and drive our success:  

  • Runner First 
    • We act in the best interest of the runner
  • Word is Bond 
    • We do what we say we'll do 
  • Champion Heart  
    • We give our all in everything we do  
  • There is no "I" in Run 
    • We stay generous with our humanity 
  • Keep Moving 
    • We find ways to move every day, because joy is kinetic!

We welcome everyone from every walk of life looking to inspire others through the power of movement - because we're all moving towards something. Let's run there.   


Your Job:

Brooks is embarking on an exciting journey to harness our data assets across a wide range of job functions-including product innovation, marketing, supply chain, customer experience, and various corporate areas such as HR, Finance, IT, and Legal. Our goal is to build and scale the data science and Machine Learning capabilities to support every corner of our operations and the communities we serve.

At Brooks, we collaborate and are super curious to explore the "art of the possible" with data and technology in service to our runners and the communities we serve. As a Senior Machine Learning (ML) Engineer, you will work closely with Data Engineers, Architects and Business stakeholders to undertake research and transition models into scalable production code. We're looking for someone who embraces ML Engineering best practices, developing high-performance, reusable code and infrastructure.
 

Note: This is an 8-month full-time temporary role.

Your Responsibilities:
Model Development & Research
  • Design, build, and test machine learning models and algorithms, within established architectures like Transformers (BERT), Deep Learning (CNNs), and Large Language Models (LLMs).
  • Conduct exploratory data analysis and drive end-to-end data science solutions for diverse business needs.
  • Lead Al strategy and implementation across cutting-edge Generative AI and RAG (Retrieval-Augmented Generation) solutions.
  • Undertake feature engineering and evaluate models for accuracy and performance.
MLOps
  • Deploy models for customers and transition them to production through MLOps, ensuring smooth integration with existing systems.
  • Implement containerization and orchestration using Docker and Kubernetes for scalable model serving.
  • Establish ongoing retraining, monitoring, and optimization of machine learning systems to maintain top performance and accuracy.
  • Leverage Infrastructure as Code (IaC) tools like Terraform to manage AI/ML infrastructure.
Collaboration & Leadership
  • Work cross-functionally with Architects, Product Managers, Data Engineering, and Business Intelligence teams to deliver integrated solutions.
  • Actively mentor and coach developers and junior designers across multiple teams.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Statistics, Data Science, Mathematics, or a related field or equivalent combination of education and/or experience.
  • 7+ years of experience in Machine Learning, Data Engineering, and Data Architecture.
  • 2+ years of hands-on experience in GenAI, NLP and Agentic AI building production grade systems.
  • Extensive experience in retail and applied consumer product industries is highly valued.
  • Strong proficiency in Python (preferred), Java, or R and SQL.
  • Deep knowledge of frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, and LangChain.
  • Hands-on experience with AWS (Bedrock, SageMaker), Azure (Databricks), or GCP (Vertex AI, BigQuery).
  • Solid understanding of probability, statistics & ML algorithms.
  • Excellent verbal and written communication skills, with the ability to break down technical topics for non-technical audiences.
  • Actively works to learn new skills to stay current with changing technologies and industry trends
  • Ability to work cross-functionally with Platform teams on enterprise initiatives and engage regularly with other architecture, security, and infrastructure teams
  • Ability to multi-task and manage multiple priorities concurrently
  • Embraces and lives Brooks values!
Compensation: The pay range for this position, based out of the Brooks Seattle HQ, is $69.76 - $111.61/hour. Pay offered will vary depending on job-related knowledge, skills, and experience.  

Other:
Brooks is proud to offer a robust benefits package to our temporary employees and their families! 
Benefits- including medical, dental, vision, HSA and employer contribution, FSA, family & fertility assistance, 401K Savings Plan and match, employee assistance program, and transportation assistance.
Paid Time Off- Eleven paid holidays and paid sick.
Perks- including product discounts, employee recognition, and fitness discounts.

Location: You will spend 4 days per week in our Seattle offices, depending on your role, as we believe our organization flourishes when connections, collaboration, creativity, problem-solving, and celebrations happen in person.


At Brooks, we celebrate diversity & equity. We are committed to creating an inclusive environment, and encourage people of all backgrounds, perspectives, experiences, and skills to apply. Brooks is proud to be an equal employment opportunity employer. All employment decisions are made without regard to race, religion, creed, color, national origin, age, sex, gender, gender identity or expression, two-spirit identity, sexual orientation, genetic information, the presence of a physical, mental, or sensory disability, marital status, pregnancy (including childbirth and related conditions), caste, citizenship or immigration status, honorably discharged veteran or military status, actual or perceived victims of domestic violence, harassment, sexual assault or stalking, HIV or Hepatitis C infection, political ideology, use of a trained service animal by a person with a disability, or on any other basis protected by federal, state, or local law, or any other non-merit based factors.

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