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Artificial Intelligence Machine Learning Engineer Jobs in Boston, MA

Artificial Intelligence (AI) Engineer

Boston, MA ยท On-site

$105K - $145K/yr

About the Role The Artificial Intelligence Engineer is responsible for developing and implementing ... generative AI, machine learning, and deep learning techniques and identifies opportunities to ...

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.

Sr. Lead Machine Learning Engineer

Cambridge, MA ยท On-site +1

$112K - $147K/yr

Sr. 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.

Senior Machine Learning Engineer

Boston, MA ยท Hybrid

$107K - $199K/yr

Senior Machine Learning Engineer Job Duties: Design and implement image processing solutions to ... We use data and analytics technologies, such as artificial intelligence (AI), and automated ...

Showing results 41-60

Artificial Intelligence Machine Learning Engineer information

See Boston, MA salary details

$34.2K

$139.9K

$210.2K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for artificial intelligence machine learning engineer in Boston, MA is $139,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,300.00 and $168,400.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

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

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

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Boston, MA look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Boston, MA are:

What cities near Boston, MA are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Boston, MA with the most Artificial Intelligence Machine Learning Engineer job openings:

Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $139,895 per year, or $67.3 per hour.

Principal Machine Learning Engineer, Foundation Models

Cambridge Mobile Telematics

Cambridge, MA โ€ข On-site

Full-time

Re-posted 11 days ago


Job description

Job Summary:
Cambridge Mobile Telematics (CMT) is the worldโ€™s largest telematics service provider, dedicated to making roads and drivers safer. They are seeking a Principal Machine Learning Engineer to lead the development of innovative AI models that enhance risk assessment, driver engagement, and crash processing using telematics data.
Responsibilities:
โ€ข Use independent judgment and discretion to lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics
โ€ข Develop and implement novel algorithms for modeling both automotive physics and human driving behavior
โ€ข Pioneer advanced self-supervised learning techniques, including the design and implementation of innovative tasks tailored to multi-modal telematics sensor data to learn rich representations of movement and driver behavior
โ€ข Develop models robust to noise, missing data, and diverse operating conditions typical of real-world mobile sensor and IoT datasets
โ€ข Build and manage scalable training and inference pipelines using tools like Ray, PyTorch DDP, Horovod, or similar frameworks
โ€ข Integrate these AIs into production systems while ensuring high performance and reliability
โ€ข Optimize these AIs for efficient deployment on various platforms, including cloud and edge/mobile devices
โ€ข Collaborate closely with engineering, product, and research teams to translate cutting-edge research into impactful products and features for the DriveWell Atlas platform
โ€ข Mentor junior scientists and contribute to the broader AI/ML strategy at CMT
โ€ข Stay abreast of the latest AI advancements, evaluating and adopting emerging technologies and methodologies relevant to telematics
โ€ข Contribute to efforts in AI explainability and interpretability
โ€ข Complete any tasks as they arise
Qualifications:
Required:
โ€ข Bachelorโ€™s degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field
โ€ข 7+ years of professional experience in AI/ML
โ€ข 3+ years of hands-on experience developing and deploying foundation models, with a strong portfolio in generative AI for sequential or spatio-temporal data
โ€ข Strong, hands-on experience in building and training time-series transformer architectures for complex sensor fusion and behavioral modeling tasks is required
โ€ข Deep expertise in designing pretraining tasks for self-supervised learning on noisy, real-world sensor data
โ€ข Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn)
โ€ข Extensive experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow for large-scale model training and deployment
โ€ข Solid understanding and practical experience with distributed training techniques and efficient training methodologies for large models
โ€ข Experience building and maintaining large-scale data processing pipelines and machine learning infrastructure using tools like Spark, Airflow, Docker, and cloud platforms (e.g., AWS, GCP, Azure)
โ€ข Excellent problem-solving skills and the ability to translate complex business problems into tractable AI-based solutions
โ€ข Strong verbal/written communication and collaboration skills, with the ability to effectively convey complex technical concepts to diverse audiences
โ€ข Product-focused thinking with a proven ability to deliver impactful AI solutions
Preferred:
โ€ข PhD or Master's degree preferred
โ€ข Experience with MLOps practices and tools for managing the lifecycle of machine learning models
โ€ข Publications in top-tier AI/ML conferences or journals
โ€ข Familiarity with techniques for model interpretability and explainability (XAI)
โ€ข Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails
Company:
Cambridge Mobile Telematics develops DriveWell, a complete telematics and behavioral analytics solution to improve safety. Founded in 2010, the company is headquartered in Cambridge, USA, with a team of 201-500 employees. The company is currently Growth Stage.