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Remote Deep Learning Engineer Jobs in Boston, MA

Redhat

Machine Learning Engineer

Boston, MA · On-site +1

$136K - $225K/yr

Apply standard software engineering practices, including version control, code reviews, and ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

eClinical Solutions

AI Engineer

Mansfield, MA · On-site +1

... frameworks, and modern Deep Learning (DL) and Machine Learning (ML) techniques in close ... for Remote Work! We have also received numerous Top Workplaces Culture Excellence Awards ...

eClinical Solutions

AI Engineer

Mansfield, MA · On-site +1

... frameworks, and modern Deep Learning (DL) and Machine Learning (ML) techniques in close ... for Remote Work! We have also received numerous Top Workplaces Culture Excellence Awards ...

Meta

Software Engineer, Systems ML

Boston, MA · On-site +1

$154K/yr

Meta is seeking an AI Software Engineer to join our Research & Development teams. The ideal ... Specialized experience in one or more of the following machine learning/deep learning domains:

Varsity Tutors

Machine Learning Tutor

Newton, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Quincy, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Cambridge, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Lynn, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Somerville, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Lowell, MA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

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All JobsDeep Learning Engineer JobsRemote Deep Learning Engineer JobsRemote Deep Learning Engineer Jobs in Boston, MA

Remote Deep Learning Engineer information

See Boston, MA salary details

$11.9K

$91.1K

$152.1K

How much do remote deep learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote deep learning engineer in Boston, MA is $91,133.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,200.00 and $151,000.00 per year, depending on experience, location, and employer.

How do Remote Deep Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

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

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What is a Remote Deep Learning Engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.
What are popular job titles related to Remote Deep Learning Engineer jobs in Boston, MA? For Remote Deep Learning Engineer jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning Engineer jobs in Boston, MA look for? The top searched job categories for Remote Deep Learning Engineer jobs in Boston, MA are:
Remote Deep Learning Engineer jobs near you
Machine Learning Engineer, Data Mining

Machine Learning Engineer, Data Mining

Motional

Boston, MA • On-site, Remote

$124K - $149K/yr

Other

Posted 20 days ago

Job description

Mission Summary:
At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.
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 Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

  • Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
  • Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
  • Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
  • Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
  • Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
  • Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.

What We're Looking For (Must-Haves):

  • BS or MS in Computer Science, Machine Learning, or a related field.
  • Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
  • Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
  • Working knowledge of version control, unit testing, and basic software design patterns.
  • Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
  • A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
  • A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.

Bonus Points (Nice-to-Haves):

  • MS/PhD in Computer Science, Machine Learning, or related field.
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
  • Background in autonomous driving, robotics, or real-time decision-making systems.
  • Familiarity with multimodal learning, sensor fusion, or embodied AI.
  • Experience building active learning loops, using the model to find the data that breaks the model.
  • Experience with ML-based data mining, active learning, or contrastive learning.
  • Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
  • Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Apply