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Remote Full Stack Machine Learning Engineer Jobs in Massachusetts

Lead Machine Learning Engineer - REMOTE

Boston, MA · On-site +1

$111K - $146K/yr

Join a Company that Empowers you to Build your Future Lennar is seeking a Machine Learning Engineer ... with full lineage and auditability. * Stand up and operate retraining pipelines using MLflow ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$140K - $190K/yr

By joining our team as a Senior Machine Learning Engineer , you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We're looking for ...

The Machine Learning Engineer (SMTS) designs and implements machine learning (ML), artificial intelligence (AI), and data science tools to projects spanning various domains. Works on exciting ...

The Machine Learning Engineer (SMTS) designs and implements machine learning (ML), artificial intelligence (AI), and data science tools to projects spanning various domains. Works on exciting ...

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 ...

Senior Full Stack Software Engineer

Boston, MA · On-site +1

$160K - $210K/yr

About the Role A growing technology startup is hiring a Senior Full Stack Software Engineer to help ... Hybrid or remote-friendly depending on location and team needs Equal Opportunity This role is with ...

Machine Learning Engineer - Cloud

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Cloud *Please consider before applying: This is a hybrid role, and candidates must reside within a commutable distance of one of our offices in either Dover, NH, or Lowell ...

The Machine Learning Engineer (SMTS) designs and implements machine learning (ML), artificial intelligence (AI), and data science tools to projects spanning various domains. Works on exciting ...

$165K - $235K/yr

We're looking for skilled Full Stack Engineers to join our growing team here at Jellyfish. We want ... Love learning new things and teaching others what you know * Strong communication skills, and enjoy ...

$133K - $175K/yr

You are fluent in Python's data and ML stack and opinionated about your preferred approaches ... Remote work : AcuityMD is committed to supporting full-remote flexibility for employees in the US.

Software Engineer

Boston, MA · On-site +1

$178K - $195K/yr

Create open-source software in the machine learning and data science pipelines domain ... Run unit tests, end-to-end tests of full stack web development in typescript, NodeJS, react and the ...

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Remote Full Stack Machine Learning Engineer information

What is a Remote Full Stack Machine Learning Engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What are some common challenges faced by remote Full Stack Machine Learning Engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

What is the difference between Remote Full Stack Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

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

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Massachusetts? The most popular types of Full Stack Machine Learning Engineer jobs in Massachusetts are:
What are popular job titles related to Remote Full Stack Machine Learning Engineer jobs in Massachusetts? For Remote Full Stack Machine Learning Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in Massachusetts look for? The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in Massachusetts are:
Infographic showing various Remote Full Stack Machine Learning Engineer job openings in Massachusetts as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.
Lead Machine Learning Engineer - REMOTE

Lead Machine Learning Engineer - REMOTE

Lennar

Boston, MA • On-site, Remote

$111K - $146K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 17 days ago


Lennar rating

7.8

Company rating: 7.8 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

25th of 78 rated construction


Job description

Lead ML Engineer - REMOTE
We are Lennar
Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States.
Join a Company that Empowers you to Build your Future
Lennar is seeking a Machine Learning Engineer to own and evolve the infrastructure and surface mechanisms that take our data science and ML models from notebook to production. This is a key role on the Applied AI & Data Science team, sitting at the intersection of software engineering, ML platform, and applied data science.
The ideal candidate is a software engineer with deep MLOps expertise. They know how to design model serving for both batch and real-time inference, build durable model registries and versioning practices, and stand up retraining pipelines that data scientists actually use. They are hands-on with AWS SageMaker (including SageMaker Unified Studio), MLflow, Weights & Biases, and the surrounding tooling that makes ML systems reliable in production.
You'll partner closely with data scientists, AI engineers, and platform teams-building and setting the foundation that lets ML models ship faster, retrain on schedule, and operate with the same engineering rigor as any other production service across 40+ divisions of one of the nation's largest homebuilders.
  • A career with purpose.
  • A career built on making dreams come true.
  • A career built on building zero defect homes, cost management, and adherence to schedules.

Your Responsibilities on the Team
  • Design, build, and set the ML platform surface used by our data science team-covering model packaging, deployment, batch and real-time inference, and observability.
  • Establish and evangelize ML platform standards, patterns, and reusable components-raising the engineering bar for how ML models are built, deployed, and operated across the organization.
  • Mentor data scientists and engineers on production ML practices, code review their platform-adjacent work, and serve as the technical authority on MLOps decisions.
  • Own model serving infrastructure on AWS SageMaker (including SageMaker Unified Studio)-building patterns for batch inference jobs, real-time endpoints, and serverless inference depending on workload requirements.
  • Build and maintain the model registry, version control, and promotion workflows that move models cleanly from development to staging to production with full lineage and auditability.
  • Stand up and operate retraining pipelines using MLflow, Weights & Biases, and orchestration tools-automating retraining triggers, experiment tracking, model evaluation, and approval gates.
  • Build monitoring and alerting for production models including drift detection, performance degradation, data quality issues, and latency or cost anomalies.
  • Write clean, modular Python and infrastructure-as-code (Terraform) for ML platform components, applying software engineering best practices including testing, versioning, and code review.
  • Partner closely with data scientists to make their workflow faster and more reliable-reducing time-to-production for new models and increasing confidence in models already in production.
  • Collaborate with Data / Platform Engineering and AI Engineering counterparts to ensure feature pipelines, model artifacts, and inference services are integrated cleanly with the broader data and AI platform.

Requirements
  • Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.
  • 7+ years of software engineering experience, including meaningful production ownership of services or platforms in a cloud environment.
  • 5+ years of hands-on MLOps or ML platform experience-deploying, monitoring, and retraining production models at scale.
  • Strong hands-on experience with AWS SageMaker (Unified Studio strongly preferred), including model training jobs, endpoints, batch transform, and pipelines.
  • Deep experience with experiment tracking, model registries, and retraining workflows using MLflow, Weights & Biases, or comparable tooling.
  • Strong Python skills with a track record of writing modular, well-tested, production-ready code; experience with infrastructure-as-code (Terraform preferred).
  • Solid understanding of both batch and real-time inference patterns, including the tradeoffs between latency, throughput, cost, and operational complexity.
  • Proven ability to partner with data scientists-understanding their workflow, lowering friction, and translating modeling needs into reliable platform capabilities.
  • Comfortable operating with autonomy in ambiguous environments-scoping work, setting realistic timelines, and raising blockers proactively without waiting to be asked.
  • Bonus: Experience with feature stores, model gateways, GPU workloads, distributed training, model drift monitoring tools, or supporting both classical ML and LLM-based models on the same platform.

What we offer:
  • The opportunity to deliver impact across one of the largest homebuilders in the United States.
  • A corporate culture focused on growth and development.
  • Freedom to try new impactful ideas.
  • Ability to deploy your work to teams across 40+ divisions and interact directly with those teams.
  • End-to-end project ownership.
  • Occasional travel for team activities and meetings.
  • Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or Dallas, TX.
  • Healthcare (medical, dental, vision) and 401k matching

  • This information is intended to be a general overview and may be modified by the company due to factors affecting the business.

General Overview of Compensation & Benefits:
We reasonably expect the base compensation offered for this position to range from an annual salary of $152,600.00 - $190,700, subject to adjustment based on business-related factors such as employee qualifications, geographic pay differentials (e.g., cost of labor/living, etc.), and operational considerations.
  • This position may be eligible for bonuses.
  • This position may be eligible for commissions.
  • This position will be eligible for the described benefits listed in the above section in accordance with Company Policy.
  • This information is intended to be a general overview and may be modified by the Company due to factors affecting the business.

Life at Lennar
At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar's policies and applicable plan terms. Visit Lennartotalrewards.com to view our suite of benefits.
Join the fun and follow us on social media to see what's happening at our company, and don't forget to connect with us on Lennar: Overview | LinkedIn for the latest job opportunities.
Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.

What Lennar employees say

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About Lennar

Sourced by ZipRecruiter

Since 1954, Lennar has built over one million new homes for families across America. We build in some of the nation’s most popular cities, and our communities cater to all lifestyles and family dynamics, whether you are a first-time or move-up buyer, multigenerational family, or Active Adult.

Industry

Construction

Company size

5,001 - 10,000 Employees

Headquarters location

Miami, FL, US

Year founded

1954

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