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Machine Learning Jobs in Federal Way, WA (NOW HIRING)

2T Consulting

Machine Learning Engineer

Seattle, WA · On-site

Build and optimize scalable machine learning pipelines for model training, deployment, monitoring, and lifecycle management. * Design and implement frameworks for multi-agent AI systems, emphasizing ...

New

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that ...

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Robinhood

Machine Learning Engineer

Bellevue, WA

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Robinhood

Machine Learning Engineer

Bellevue, WA · On-site

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Hive

Machine Learning Engineer

Seattle, WA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Unitytech

Machine Learning Engineer

Bellevue, WA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Hive

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Apple

Machine Learning Engineer

Seattle, WA

$175K - $308K/yr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision 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 ...

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 ...

PitchBook Data

Machine Learning Engineer

Seattle, WA · On-site

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

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All JobsMachine Learning JobsMachine Learning Jobs in Federal Way, WA

Machine Learning information

See Federal Way, WA salary details

$28.5K

$47.6K

$98.3K

How much do machine learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for machine learning in Federal Way, WA is $47,555.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,300.00 and $51,400.00 per year, depending on experience, location, and employer.

What is a machine learning?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are the typical day-to-day responsibilities in a machine learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in a machine learning position?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are popular job titles related to Machine Learning jobs in Federal Way, WA? For Machine Learning jobs in Federal Way, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning jobs in Federal Way, WA look for? The top searched job categories for Machine Learning jobs in Federal Way, WA are:
What cities near Federal Way, WA are hiring for Machine Learning jobs? Cities near Federal Way, WA with the most Machine Learning job openings:
Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Federal Way, WA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $47,555 per year, or $22.9 per hour.

Machine Learning Engineer

2T Consulting

Seattle, WA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Responsibilities
  • Design, develop, and maintain high-performance distributed systems to support large-scale machine learning inference and data processing.
  • Build and optimize scalable machine learning pipelines for model training, deployment, monitoring, and lifecycle management.
  • Design and implement frameworks for multi-agent AI systems, emphasizing state management, reliability, and long-running autonomous workflows.
  • Architect and enhance Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to improve model accuracy, relevance, and response quality.
  • Develop platform-level tools for prompt engineering, automated evaluation, prompt optimization, and experimentation.
  • Deploy, monitor, and maintain machine learning and generative AI models in production environments.
  • Implement robust MLOps practices, including model versioning, observability, monitoring, and automated deployment pipelines.
  • Collaborate with cross-functional teams to design, develop, and deliver AI-powered products and services.
  • Optimize system performance, scalability, and reliability for high-volume production workloads.
  • Stay current with emerging technologies, frameworks, and best practices in machine learning and generative AI.
Required Qualifications
  • Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Software Engineering, or a related field (or equivalent practical experience).
  • 5+ years of experience in machine learning engineering, software engineering, or related technical roles.
  • Strong experience designing and developing distributed systems and scalable backend architectures.
  • Deep understanding of the end-to-end machine learning lifecycle, including data ingestion, model training, evaluation, deployment, monitoring, and maintenance.
  • Hands-on experience building applications using Large Language Models (LLMs), including Retrieval-Augmented Generation (RAG) architectures and advanced prompt engineering techniques.
  • Experience deploying, scaling, and maintaining machine learning models in production environments.
  • Strong programming skills in Python.
  • Experience with modern machine learning frameworks such as PyTorch.
  • Strong understanding of software engineering best practices, including testing, version control, and code quality.
  • Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications
  • Experience with distributed task queues or workflow orchestration frameworks for managing complex, multi-stage AI processes.
  • Experience with frameworks that support horizontal scaling of compute-intensive machine learning workloads.
  • Knowledge of agentic AI architectures, including multi-agent systems, tool integration, self-correction, and iterative reasoning workflows.
  • Familiarity with vector databases, embedding technologies, and high-throughput data processing pipelines.
  • Experience implementing MLOps practices, CI/CD pipelines, and cloud-based machine learning infrastructure.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes.

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