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Senior Staff Machine Learning Engineer Jobs in Boston, MA

Lead Machine Learning Engineer

Cambridge, MA ยท On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and ...

Lead Machine Learning Engineer (IC)

Cambridge, MA ยท On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

Machine Learning Engineer

Boston, MA ยท On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Showing results 41-60

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 Sep 3, 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 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 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 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 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 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:

Infographic showing various Senior Staff Machine Learning Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 2% As Needed, 76% Full Time, 16% Part Time, 1% Temporary, and 5% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $137,492 per year, or $66.1 per hour.

Senior Machine Learning Engineer - Hybrid

Manulife

Boston, MA โ€ข On-site, Remote

$175K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

Employer: John Hancock Life Insurance Company (USA)

Job Site: 200 Berkeley Street, Boston, MA 02116

Job Title: Senior Machine Learning Engineer

Job Duties:

Package models, automate workflows, and operationalize analytics solutions to generate business value for organization's insurance division as member of U.S. based Advanced Analytics Team. Duties include:

  • Design, recommend, and implement platforms and infrastructure using MLOps/LLMOps best practices;
  • Collaborate with data scientists and data engineers to design and implement scalable and efficient machine learning pipelines;
  • Evaluate and optimize machine learning models for performance and scalability;
  • Deploy machine learning models into production and monitor performance;
  • Manage data science infrastructure to streamline model development and deployment;
  • Support development and deployment of high-quality Generative AI technologies including prompt engineering and RAG applications, and fine-tuning LLM models using Azure AI Studio;
  • Propose appropriate tools including languages, libraries, and frameworks for implementing projects;
  • Work closely with infrastructure architects to design scalable and efficient solutions;
  • Collaborate with cross-functional teams to integrate machine learning models into existing systems and processes;
  • Keep abreast of latest advancements in machine learning, MLOps, and LLMOps techniques, and contribute to continuously improving organization's machine learning capabilities; and
  • Mentor associates and peers on MLOps best practices.

Work Arrangement requirement: Hybrid from Boston office (3 days from office, 2 days from home)

Minimum Requirements:

Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

Minimum Requirements:

Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

Minimum Requirements:

Master's degree or foreign equivalent in Data Science, Computer Science, Computer Engineering, or related field and 3 years of machine learning experience.

Experience must include the following, which may be gained concurrently:

  • 3 years of experience developing and deploying machine learning models for model training, optimization, evaluation, and production deployment through APIs, microservices, or cloud-based serving infrastructure using Python, TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
  • 3 years of experience deploying and managing infrastructure using Linux OS, containerization technologies (Docker, Kubernetes), relational databases (PostgreSQL, MySQL, and Oracle) and NoSQL databases (MongoDB, Cassandra, Elasticsearch and Redis) using AWS, Azure or GCP cloud platforms.
  • 3 years of experience designing and building scalable ETL pipelines and feature engineering workflows for large-scale datasets using distributed processing frameworks including Apache Spark (PySpark, Spark SQL), Hadoop ecosystem tools, or cloud-based big data services including Databricks and EMR.
  • 2 years of experience developing and deploying Large Language Models including BERT, GPT-series, T5, or LLaMA, or other transformer-based NLP models using cloud-based platforms and open-source frameworks.
  • 3 years of experience designing hybrid machine learning systems combining rule-based decision engines with ML models for fraud detection, compliance, claims adjudication, or automated decision-making in regulated environments.
  • 3 years of experience applying machine learning algorithms, statistical modeling, and data analysis techniques for model optimization, generating actionable insights, and working with structured and unstructured data to solve business problems in financial services, fintech, insurance, or other regulated industries.
  • 3 years of experience with Agile development methodologies including Scrum, Kanban, or SAFe for sprint planning, iterative development cycles, and cross-functional team collaboration in enterprise environments.
  • 2 years of experience developing and deploying computer vision models for document processing, OCR, information extraction, or image classification using OpenCV, Tesseract, or cloud-based vision APIs.

Salary: $175,000 per year

    The role being advertised is an existing vacancy.

    About Manulife and John Hancock

    Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

    Manulife is an Equal Opportunity Employer

    At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

    It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.

    Referenced Salary Location

    Boston, Massachusetts

    Working Arrangement

    Hybrid

    Salary range is expected to be between

    $107,450.00 USD - $199,550.00 USD

    Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.

    Manulife/John Hancock offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, and we offer the full range of statutory leaves of absence.

    We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.

    Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify

    Company: John Hancock Life Insurance Company (U.S.A.)