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Artificial Intelligence Machine Learning Engineer Jobs in Framingham, MA

Capital One

Lead Machine Learning Engineer

Cambridge, MA · 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 ...

WilmerHale

Artificial Intelligence (AI) Engineer

Boston, MA · 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 ...

Capital One

Lead Machine Learning Engineer (IC)

Cambridge, MA · 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.

Capital One

Sr. Lead Machine Learning Engineer

Cambridge, MA · 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.

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All JobsArtificial Intelligence Machine Learning Engineer JobsArtificial Intelligence Machine Learning Engineer Jobs in Framingham, MA

Artificial Intelligence Machine Learning Engineer information

See Framingham, MA salary details

$32.4K

$132.5K

$199K

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

As of Aug 21, 2026, the average yearly pay for artificial intelligence machine learning engineer in Framingham, MA is $132,454.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,400.00 and $159,400.00 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 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 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 popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Framingham, MA?

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

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

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

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Framingham, MA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $132,454 per year, or $63.7 per hour.

Physical Artificial Intelligence Architect - AI

Motion Recruitment Partners, LLC

Boston, MA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago

Job description

Join a rapidly growing, venture-backed robotics company that's transforming warehouse automation through advanced AI, robotics, and autonomous systems. With cutting-edge robotic platforms already deployed in real-world logistics environments, this organization is focused on solving some of the industry's most challenging manipulation and automation problems using modern machine learning and control techniques.
This is an opportunity to bridge cutting-edge AI research with production robotics. You'll help define the next generation of robotic autonomy, applying state-of-the-art learning algorithms to systems operating at commercial scale where reliability, speed, and robustness matter every day.
The Opportunity
We're seeking a Physical AI Architect to serve as the technical leader responsible for the architecture of next-generation robotic autonomy systems. This role combines deep expertise in machine learning, robotics, perception, planning, and controls with the practical experience required to deploy AI-powered systems onto production hardware.
You'll work across robotics software, perception, controls, embedded systems, and mechanical engineering to develop scalable autonomy solutions that improve robotic performance while mentoring senior engineers and influencing the long-term technical strategy of the organization.
Required Skills & Experience
  • MS or PhD in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
  • 8+ years of experience developing robotics, autonomy, or AI-powered systems
  • Demonstrated history of deploying AI solutions into production robotic hardware
  • Deep expertise with diffusion models and modern robot learning techniques
  • Strong background in optimal control, Model Predictive Control (MPC), trajectory optimization, and feedback control systems
  • Experience combining machine learning with traditional robotics planning and control architectures
  • Strong Python and C++ programming skills
  • Experience with ROS2 or equivalent robotics middleware
  • Hands-on experience integrating sensors, embedded compute platforms, and robotic actuators
  • Experience deploying AI models under real-time performance constraints
  • Excellent communication and technical leadership skills
Desired Skills & Experience
  • Experience with diffusion policies, score-based generative models, and behavior cloning
  • Experience deploying AI models on NVIDIA Jetson, ARM-based platforms, GPUs, or edge computing devices
  • Experience with RGB-D cameras, force/torque sensors, encoders, and multi-modal sensor fusion
  • Experience designing scalable perception, planning, and controls architectures
  • Familiarity with reinforcement learning and imitation learning
  • Experience optimizing inference latency and real-time robotic performance
  • Strong systems engineering mindset with experience designing highly reliable autonomous systems
  • Previous experience mentoring senior engineers or leading technical initiatives
What You Will Be Doing
  • Architect the company's next-generation Physical AI platform spanning perception, planning, and robotic controls
  • Lead development of diffusion-based policy learning solutions for robotic manipulation and automation
  • Design autonomous systems that combine modern AI approaches with classical control algorithms
  • Define technical strategy for integrating machine learning into production robotic systems
  • Collaborate with perception, controls, firmware, mechanical, and embedded engineering teams to optimize complete robotic solutions
  • Drive hardware integration across sensors, embedded compute, and actuator platforms
  • Improve system throughput by optimizing model inference, planning performance, and hardware execution
  • Evaluate emerging AI technologies and determine practical applications for production robotics
  • Mentor senior engineers and establish technical best practices across autonomy development
  • Help shape the long-term AI and robotics roadmap for future product generations
Tech Breakdown
  • 35% AI & Robot Learning (Diffusion Models, ML)
  • 25% Robotics Planning & Optimal Control
  • 20% Software Architecture & Systems Design
  • 10% Hardware Integration & Embedded Systems
  • 10% Technical Leadership & Mentorship
Daily Responsibilities
  • 50% Hands-On AI & Robotics Development
  • 20% Architecture & Technical Strategy
  • 15% Cross-Functional Engineering Collaboration
  • 10% Performance Optimization & Hardware Integration
  • 5% Mentoring & Technical Leadership
The Offer
  • Competitive base salary plus bonus and equity potential
  • Comprehensive medical, dental, and vision insurance
  • 401(k) with company contribution
  • Unlimited PTO and paid holidays
  • Opportunity to work on cutting-edge AI-powered robotics deployed in real-world production environments
  • Collaborative engineering culture with significant technical ownership
  • Career growth within a rapidly scaling, venture-backed robotics company

Applicants must be currently authorized to work in the United States on a full-time basis. Sponsorship may be considered for highly qualified candidates.

Apply