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Product Manager Machine Learning Jobs in Washington

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

VivSoft Technologies

Product Manager

Springfield, VA · On-site

... machine learning products within a secure digital intelligence environment. The ideal candidate ... Product Management, Agile, or Project Management certification (e.g., Scrum Master, PMP, SAFe ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Own ML projects from initial research and prototyping through production deployment and monitoring.

AISquared

Machine Learning Engineer

Washington, DC · On-site

... Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ... and product teams to ensure reliable and efficient solutions. Responsibilities : • Design ...

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All JobsProduct Machine Learning JobsProduct Manager Machine Learning JobsProduct Manager Machine Learning Jobs in Washington

Product Manager Machine Learning information

See Washington salary details

$58.3K

$180.5K

$223.1K

How much do product manager machine learning jobs pay per year?

As of Jul 10, 2026, the average yearly pay for product manager machine learning in Washington is $180,541.00, according to ZipRecruiter salary data. Most workers in this role earn between $159,700.00 and $223,100.00 per year, depending on experience, location, and employer.

What is the AI PM salary?

The salary for a Product Manager specializing in Machine Learning typically ranges from $100,000 to $160,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, often including bonuses and stock options. Strong knowledge of AI tools and data-driven decision-making are common requirements for this role.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers or AI research directors, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with significant experience and leadership responsibilities.

How does a Product Manager specializing in Machine Learning typically collaborate with data scientists and engineering teams?

Product Managers in Machine Learning work closely with both data scientists and engineering teams to translate business objectives into viable AI-driven products. They facilitate communication by defining clear requirements, prioritizing features, and ensuring that the technical roadmap aligns with user needs and company strategy. Regular meetings, progress reviews, and shared documentation are common practices to keep everyone aligned. This cross-functional collaboration is essential for addressing feasibility, optimizing models, and delivering successful products on schedule.

What does a machine learning product manager do?

A machine learning product manager oversees the development and deployment of AI and machine learning products, coordinating between data scientists, engineers, and stakeholders. They define product requirements, prioritize features, and ensure that machine learning models meet business goals and performance standards, often using tools like data analysis and model monitoring platforms.

What does a Product Manager for Machine Learning do?

A Product Manager for Machine Learning oversees the development and deployment of machine learning products or features. They work closely with data scientists, engineers, and business stakeholders to identify opportunities where machine learning can deliver value, define product requirements, and guide projects from conception to launch. Their responsibilities include setting the product vision, prioritizing features, ensuring alignment with business goals, and evaluating the impact of machine learning solutions. They also help bridge the gap between technical teams and non-technical stakeholders by translating complex concepts into actionable plans.

Which 3 jobs will survive AI?

Product Managers in machine learning will continue to be essential as they oversee AI projects, coordinate teams, and ensure alignment with business goals. Roles requiring complex problem-solving, creativity, and human judgment—such as data scientists and AI ethics specialists—are also likely to persist. These jobs demand skills that are difficult for AI to fully replicate, including strategic thinking and interpersonal communication.

What is the difference between Product Manager Machine Learning vs Data Scientist?

AspectProduct Manager Machine LearningData Scientist
Primary FocusOverseeing ML product development, strategy, and deploymentAnalyzing data, building models, and deriving insights
Required SkillsProduct management, ML understanding, cross-functional collaborationStatistics, programming, data analysis
Work EnvironmentProduct teams, engineering, business stakeholdersData analysis teams, research, engineering
Common CertificationsProduct management certifications, ML coursesData science certifications, programming skills

While both roles involve machine learning, Product Manager Machine Learning focuses on guiding ML products from conception to deployment, working closely with engineering and business teams. Data Scientists primarily analyze data and develop models to extract insights. The roles complement each other but differ in their core responsibilities and skill sets.

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

To thrive as a Product Manager, Machine Learning, you need a solid understanding of product lifecycle management, data analytics, and machine learning concepts—often supported by a technical degree and relevant experience. Familiarity with tools like Python, SQL, JIRA, and machine learning frameworks, as well as certifications such as PMP or Agile, is highly beneficial. Outstanding communication, stakeholder management, and problem-solving skills help you bridge the gap between technical teams and business objectives. These abilities are crucial to successfully guide ML products from ideation to launch, ensuring they deliver real value and align with organizational goals.
What are popular job titles related to Product Manager Machine Learning jobs in Washington? For Product Manager Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Product Manager Machine Learning jobs in Washington look for? The top searched job categories for Product Manager Machine Learning jobs in Washington are:
What cities in Washington are hiring for Product Manager Machine Learning jobs? Cities in Washington with the most Product Manager Machine Learning job openings:
Product Manager Machine Learning jobs near you
Infographic showing various Product Manager Machine Learning job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $180,541 per year, or $86.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Spear AI

Washington, DC • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago

Job description

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions that support our nation's security. As we expand, we're building a culture where innovation meets mission-critical work. We operate with a flat organizational structure that empowers every team member to make an impact, collaborate directly with leadership, and contribute to projects that matter. Whether you're joining our Hardware, Software, or Services division, you'll work alongside talented professionals who are committed to excellence and advancing the capabilities that keep our nation safe and secure.
Spear AI builds sonobuoy sensors that are deployed into the water and collect edge data. We also work with the U.S. Navy to collect and process their SONAR data. You'll have an opportunity to work on real-world projects that directly impact warfighter capabilities and mission success.
What You'll Do
  • We're a small team wearing many hats, and you'd have a wide variety of responsibilities that include:
  • Design, train, and optimize machine learning models using PyTorch
  • Deploy models to production environments in the cloud and at the edge
  • Build and maintain ML pipelines for training, evaluation, and inference
  • Integrate machine learning models into real-time and batch processing systems
  • Optimize model performance for accuracy, latency, and resource constraints
  • Implement model monitoring, versioning, and deployment strategies
  • Work with signal processing data and time-series analysis
  • Improve local development and CI/CD for ML workflows using modern tooling and GitHub Actions
Who You Are
  • We're looking for someone with strong Machine Learning Engineering skills who shares our most important values:
  • You're fanatical about polish. Every detail matters. You love to make sure your code is linted, formatted, fully typed, and has comprehensive test coverage.
  • You care about correctness. You take pride in the fact that your models perform reliably and downstream consumers trust your predictions.
  • You obsess over performance. You daydream about model latency, throughput, and efficient inference pipelines.
  • You dive deep. It's important for you to really know how things work. You're always building prototypes and setting up experiments to reinforce your understanding.
  • You live on the bleeding edge. You've got a long list of upcoming ML techniques and frameworks you're excited about and can't wait to experiment with new approaches.
  • You're a great teacher. You know how to break down complex ML concepts for a specific audience and make it click with them in a way that gets them excited.
Why Work With Us
  • We ship - We don't work on 18-month projects that are irrelevant before they're even finished.
  • Our work has impact - We build products that are deployed to U.S. submarines and integrate with the sonobuoys we manufacture.
  • We're growing responsibly - We have the resources to hire a lot more people, but we don't want to build a massive team of people who don't share our values.
  • We're remote - Work from wherever you want. We collaborate in real time on Slack or asynchronously via GitHub.
  • We're profitable - We aren't burning through cash trying to make the business work. But we also have investors who believe in us and are committed to our success.
  • We care about doing great work - You don't need permission to sweat the details here.
  • We don't take ourselves too seriously - We're building products that make the world safer. But we don't let that get to our heads.
Important Skills
  • Several years of experience with Python and machine learning frameworks
  • Expertise in PyTorch for building and training neural networks
  • Experience training and serving models in cloud environments (AWS, Azure, GCP)
  • Proficiency with MLOps practices including experiment tracking, model versioning, and deployment
  • Experience with model optimization for production performance and scale
  • Knowledge of Docker and Kubernetes for containerized deployments
  • Familiarity with REST APIs and model serving frameworks
  • Understanding of CI/CD pipelines for ML systems
  • Strong fundamentals in machine learning including model architecture design, training strategies, and evaluation
Nice To Have
  • Experience with reinforcement learning algorithms and applications
  • Digital signal processing experience
  • Background in time-series analysis or sensor data processing
  • Experience with edge deployment and model optimization for resource-constrained environments
  • Familiarity with distributed training across multiple GPUs/nodes
  • Experience with model compression techniques (quantization, pruning, distillation)
  • Contributions to open-source ML projects or research publications
  • Experience in defense, aerospace, or other regulated industries
What We Offer
  • Unlimited PTO - Take the time you need to recharge and maintain work-life balance.
  • Dedicated Sick Time - Your health and well-being come first.
  • Comprehensive Health & Benefits - Medical, dental, and vision coverage to keep you and your family protected.
  • 11 Paid Holidays - Enjoy time off throughout the year to celebrate and spend with loved ones.
  • Professional Development - Educational opportunities and resources to help you grow your skills and advance your career.
  • Collaborative Environment - Work directly with leadership in our flat organizational structure, where your ideas and contributions matter.
  • Mission-Driven Work - Contribute to projects that directly support national security and make a real-world impact.
  • Growth Opportunities - Join us during an exciting expansion phase where you can help shape our future.
Additional Benefit Opportunities When You Choose Spear AI:
  • 401(k) with company match
  • Onsite / Remote / Flexible work arrangements or hybrid options (position dependent)
  • Relocation assistance (position dependent)
  • Referral bonuses
  • Performance bonuses
  • Life insurance and disability coverage
  • Technology home office setup stipend
  • Professional certification reimbursement (position dependent)
We offer competitive compensation tailored to your experience, location, and the impact you'll make. We're committed to equitable pay and will share a range aligned to your level and geography during the hiring process. In accordance with state law, candidates in jurisdictions such as CA, CO, WA, NY, and others, where applicable, will be provided a good-faith salary range upon request and through the hiring process. This is a full-time, exempt position under the Fair Labor Standards Act (FLSA) and is not eligible for overtime pay.

Compensation for this position is provided on a salaried basis and is not subject to reduction based on hours worked. At Spear AI, you'll find more than just a job; you'll join a mission-driven team where your work directly contributes to national security. Our flat organizational structure means your voice matters, your ideas reach leadership, and your impact is visible. As we grow, we're committed to building robust processes and infrastructure that support both our mission and our people. We value collaboration, continuous improvement, and the expertise each team member brings to the table. If you're looking for a place to grow professionally while working on projects that truly matter, we'd love to hear from you.

You must be willing to receive a Secret or Top Secret/SCI security clearance. This will be at no expense to you. For resources on what goes into a security background investigation and what disqualifies people reference the CIA requirements.
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About Spear AI

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Washington, DC, US

Year founded

2020

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