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Machine Learning Jobs in Spokane, WA (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Spokane, WA

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Itron, Inc

Data Science Analyst

Liberty Lake, WA · On-site

$75K - $130K/yr

Develop, validate, and deploy statistical and machine learning models to improve forecasting accuracy across revenue and expense categories in a complex Utilities & Energy business environment.

micro1 AI

Corporate Counsel - Remote

Spokane, WA · Remote

$100 - $150/hr

Develop case strategies and motion practice templates that inform machine learning models in legal contexts. * Continuously review and refine rubric criteria to align with evolving legal standards ...

micro1 AI

Attorney - Remote

Spokane, WA · Remote

$100 - $150/hr

Develop case strategies and motion practice templates that inform machine learning models in legal contexts. * Continuously review and refine rubric criteria to align with evolving legal standards ...

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All JobsMachine Learning JobsMachine Learning Jobs in Spokane, WA

Machine Learning information

See Spokane, WA salary details

$25.8K

$43.1K

$89K

How much do machine learning jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning in Spokane, WA is $43,057.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,900.00 and $46,500.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer, AI research director, or chief AI officer, often requiring advanced skills in deep learning, data analysis, and programming. These roles usually involve leadership responsibilities, strategic planning, and may require extensive experience and specialized certifications, with compensation reflecting the seniority and impact of the role.

What is a Machine Learning job?

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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn salaries of $500,000 or more, especially when including bonuses and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of impactful projects.

What are some 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 jobs 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 the Machine Learning position, and why are they important?

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.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI ethics specialists are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require specialized skills, critical thinking, and understanding of complex algorithms that are difficult to fully automate. Continuous learning and certification in relevant tools like Python, TensorFlow, or ethical frameworks will support job security in these fields.
What are the most commonly searched types of Machine Learning jobs in Spokane, WA? The most popular types of Machine Learning jobs in Spokane, WA are:
What are popular job titles related to Machine Learning jobs in Spokane, WA? For Machine Learning jobs in Spokane, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning jobs in Spokane, WA look for? The top searched job categories for Machine Learning jobs in Spokane, WA are:
What cities near Spokane, WA are hiring for Machine Learning jobs? Cities near Spokane, WA with the most Machine Learning job openings:
Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Spokane, WA as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $43,057 per year, or $20.7 per hour.

Machine Learning Engineer

Bespoke Labs

Spokane, WA

Full-time

Posted 3 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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