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Senior Staff Machine Learning Engineer information

See Boston, MA salary details

$64.6K

$137.5K

$199.4K

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

As of Jul 29, 2026, the average yearly pay for senior staff machine learning engineer in Boston, MA is $137,492.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $155,900.00 per year, depending on experience, location, and employer.

What are the primary challenges a Senior Staff Machine Learning Engineer faces when leading large-scale ML projects?

Senior Staff Machine Learning Engineers often navigate complex challenges such as aligning cross-functional teams, ensuring model scalability, and maintaining data integrity across evolving pipelines. They are responsible for setting technical direction, mentoring junior engineers, and driving collaboration between data scientists, software engineers, and product managers. Balancing hands-on technical work with high-level architectural decisions, while also keeping up with rapid advancements in the field, is key to success in this role.

What does a Senior Staff Machine Learning Engineer do?

A Senior Staff Machine Learning Engineer leads the design, development, and deployment of complex machine learning systems within an organization. They work closely with cross-functional teams to identify business challenges that can be addressed with machine learning and guide the technical strategy for implementing solutions. Their responsibilities often include mentoring junior engineers, setting best practices, overseeing large-scale projects, and ensuring models are robust, scalable, and ethically implemented. Additionally, they may contribute to research and development, staying up-to-date with the latest advancements in the field.

What is the difference between Senior Staff Machine Learning Engineer vs Machine Learning Engineer?

AspectSenior Staff Machine Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's/PhD in CS, AI, or related; experience in ML frameworksBachelor's/Master's in CS, AI, or related; some experience in ML
Work EnvironmentLeadership roles, cross-team collaboration, strategic planningImplementation, model development, experimentation
Industry UsageTech companies, research labs, large enterprisesStartups, tech firms, research projects

The Senior Staff Machine Learning Engineer typically holds a more senior, strategic role with leadership responsibilities, while the Machine Learning Engineer focuses on developing and deploying ML models. Both roles require strong technical skills, but the senior position involves guiding projects and mentoring teams.

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

To thrive as a Senior Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, software engineering, and a relevant advanced degree (often MS or PhD). Mastery of tools such as Python, TensorFlow, PyTorch, distributed computing frameworks, and experience with cloud platforms is typically required. Strong leadership, communication, and project management skills distinguish top performers in this role. These abilities are crucial for designing scalable ML solutions, leading teams, and driving impactful business outcomes.
What are popular job titles related to Senior Staff Machine Learning Engineer jobs in Boston, MA? For Senior Staff Machine Learning Engineer jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Senior Staff Machine Learning Engineer jobs in Boston, MA look for? The top searched job categories for Senior Staff Machine Learning Engineer jobs in Boston, MA are:
Senior Staff Machine Learning Engineer jobs near you
Infographic showing various Senior Staff Machine Learning Engineer job openings in Boston, MA as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $137,492 per year, or $66.1 per hour.
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Xometry

Waltham, MA

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago

Job description

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You will lead the design and delivery of complex ML systems, architect integrations across our tech stack, and set the engineering standard for how we build and deploy machine learning solutions at scale. You will work closely with data scientists, engineers, and product managers to bring high-impact ML capabilities into production. Everything you build will matter. A defining piece of this role is owning the AI/ML architecture behind one of Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration. You will be the data engineering lead for the digital thread that connects Xometry's platform to our partner's ecosystem - Solid Edge, NX, Designcenter, and Teamcenter - building the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between the two systems in real time. The system you design is what takes the innovative digital thread operating at "science fiction speed" from ideation to reality.

How You'll Contribute:

  • Lead with technical depth - Own the end-to-end lifecycle from requirements gathering through release, ensuring high-quality, on-time delivery across complex, cross-functional initiatives
  • Own the Partner integration AI/ML plane - Architect and build the high-performance AI/ML layer of Xometry's embedded DFM AI + IQE integration with Teamcenter and  Designcenter. You will be responsible for designing the real-time ML serving architecture and the low-latency signal path that delivers DFM and pricing feedback directly into the designer's environment. This includes defining the data contracts for model inputs/outputs and implementing the MLOps, governance, and observability required for a mission-critical, public-marketplace partner integration.
  • Build for scale - Develop cloud-based production systems powering real-time endpoints and MLOps, integrated with Xometry's broader systems and infrastructure
  • Solve ambiguous problems - Navigate complex, cross-domain technical challenges, evaluate variable factors, and deliver solutions that meet both business and technical objectives
  • Set the Standard - Proactively surface opportunity areas, take ownership of new processes and solutions, and develop multi-quarter roadmaps to accomplish key technical objectives
  • Champion quality and security - Apply best practices in automated testing, parallel and distributed computing, and secure software development across ML systems
  • Collaborate broadly - Partner with engineers, product managers, data scientists, and business stakeholders to translate requirements into robust technical solutions
  • Mentor and elevate - Guide other engineers through design reviews, code reviews, and technical mentorship, raising the overall capability of the team
  • Stay current - Keep pace with advances in ML/AI and bring relevant new approaches, tools, and frameworks into practice

What You'll Bring to Xometry:

  • Bachelor's degree in a STEM field (or equivalent experience) plus 6-8 years of experience in machine learning engineering, with a track record of owning and delivering complex ML systems in production
  • Deep expertise in ML and AI technologies, including Gradient Boosting methods, Deep Learning, and/or Generative AI frameworks, with a focus on backend scalability and reusability
  • Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred), including auto-scaling, monitoring, and alerting
  • Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar
  • Solid grounding in software engineering fundamentals, data structures, and algorithms
  • Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines
  • Proficiency with CI/CD pipelines (e.g., Github actions),test driven development, and infrastructure as code (e.g., Terraform).
  • Experience profiling and optimizing existing ML model deployments for latency and throughput
  • Ability to operate independently on new and ambiguous assignments, determine methods and procedures, and communicate effectively across engineering, product, and business audiences
  • Experience with state-of-the-art modeling techniques including transformers, self-supervised pre-training, large language models (LLMs), or generative AI
  • Knowledge of containers, container orchestration (Kubernetes), and cloud-native distributed systems
  • Background in manufacturing, supply chain, or marketplace environments is a plus - but curiosity and drive matter more

The estimated base salary range for new hires into this role is $200,000-$220,000.00 annually + bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

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About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013

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