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Freelance Google Machine Learning Engineer Jobs in Boston, MA

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.

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.

Machine Learning Engineer II

Cambridge, MA

$106K - $145K/yr

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization ...

Lead Machine Learning Engineer

Cambridge, MA · On-site

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud ...

Lead Machine Learning Engineer

Cambridge, MA

$112K - $147K/yr

Lead Machine Learning Engineer At Capital One, we are changing banking for good by creating ... Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

About the position: We're looking for a Senior Machine Learning Engineer with deep expertise in some area of ML engineering to join our growing ML team and work closely with our software and computer ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

Overview: The ASUS Robotics & AI Center is seeking a Senior Machine Learning Engineer to join our global research and development team. This role centers on leading the design and delivery of ...

Showing results 41-60

Freelance Google Machine Learning Engineer information

See Boston, MA salary details

$16

$51

$143

How much do freelance google machine learning engineer jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for freelance google machine learning engineer in Boston, MA is $51.83, according to ZipRecruiter salary data. Most workers in this role earn between $26.39 and $67.12 per hour, depending on experience, location, and employer.

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

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

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Boston, MA?

The most popular types of Google Machine Learning Engineer jobs in Boston, MA are:

What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Boston, MA?

For Freelance Google Machine Learning Engineer jobs in Boston, MA, the most frequently searched job titles are:

What cities near Boston, MA are hiring for Freelance Google Machine Learning Engineer jobs?

Cities near Boston, MA with the most Freelance Google Machine Learning Engineer job openings:

Staff Machine Learning Engineer

Xometry

Waltham, MA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 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.

#LI-Hybrid


Xometry logo

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