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Director Machine Learning Jobs in Canton, MA (NOW HIRING)

Chewy

Associate Director, Data Science

Boston, MA

Your Opportunity Chewy is seeking an innovative and strategic Associate Director, Data Science to ... In this role, you will lead a high-performing team of Data Scientists and Machine Learning ...

Amgen

Senior Director - BioIntelligence

Cambridge, MA · On-site

The BioIntelligence team applies machine learning, statistical modeling, and generative AI ... directing the allocation or resources. Your managerial experience may run concurrently with the ...

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All JobsMachine Learning JobsDirector Machine Learning JobsDirector Machine Learning Jobs in Canton, MA

Director Machine Learning information

See Canton, MA salary details

$38.1K

$97.2K

$149.1K

How much do director machine learning jobs pay per year?

As of Jun 16, 2026, the average yearly pay for director machine learning in Canton, MA is $97,210.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,600.00 and $112,100.00 per year, depending on experience, location, and employer.

What is a $900,000 AI job?

A $900,000 AI job typically refers to senior roles such as Director of Machine Learning or Chief AI Officer, which involve leading AI strategy, managing teams, and developing advanced models. These positions often require extensive experience, expertise in machine learning frameworks, and strong leadership skills, with compensation reflecting high-level responsibilities and industry demand.

Which 3 jobs will survive AI?

For a Director of Machine Learning, roles that require complex problem-solving, strategic oversight, and domain expertise are likely to persist, such as AI research scientists, data science managers, and AI ethics specialists. These positions involve high-level decision-making, creativity, and understanding of nuanced human contexts that are difficult for AI to fully replicate. Skills in leadership, critical thinking, and advanced technical knowledge will remain valuable in these roles.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like ML Engineer or Data Scientist, are generally among the higher-paying jobs in the tech industry due to the specialized skills required, such as programming, statistics, and experience with tools like TensorFlow or PyTorch. Salaries vary based on experience, location, and company size but tend to be significantly above average for many other roles in technology and data analysis.

What are the key skills and qualifications needed to thrive in the Director Machine Learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

How much does an AI director make?

An AI director's salary typically ranges from $120,000 to $200,000 annually, depending on experience, industry, and location. Senior roles with advanced skills in machine learning, deep learning, and leadership often command higher compensation, especially in tech hubs or large organizations.

What is a Director Machine Learning job?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a Director of Machine Learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What cities near Canton, MA are hiring for Director Machine Learning jobs? Cities near Canton, MA with the most Director Machine Learning job openings:
Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in Canton, MA as of June 2026, with employment types broken down into 64% Full Time, 24% Part Time, 10% Temporary, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $97,210 per year, or $46.7 per hour.
Senior Machine Learning Engineer, Data Mining

Senior Machine Learning Engineer, Data Mining

Motional

Boston, MA • On-site, Remote

$133K - $175K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 5 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 Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.
What You'll Do:
  • Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
  • Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
  • Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
  • Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
  • Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
  • Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.
What We're Looking For:
  • BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
  • 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
  • Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
  • Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
  • Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
  • Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
  • Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
  • Demonstrated ability to ship production-grade ML systems and mentor team members.
  • Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers
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.
  • Publications or open-source contributions in RL, distillation, or efficient ML.

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.
The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.
Salary Range
$172,000-$229,000 USD
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.
Our journey is always people first.
We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.
Higher purpose, greater impact.
We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.
Scale up, not starting up.
Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.
Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

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