ZipRecruiter

Log In

1

Phd Machine Learning Jobs in Boston, MA (NOW HIRING)

Chewy

Senior Machine Learning Engineer

Boston, MA · On-site +1

$149K - $245K/yr

Machine learning and deep-learning models will influence selection, relevance, ranking, click ... S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data ...

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site +1

$124K - $149K/yr

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 ...

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site +1

$144K - $192K/yr

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 ...

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site +1

$144K - $192K/yr

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 ...

Motional

Machine Learning Systems Engineer

Boston, MA · On-site +1

$144K - $192K/yr

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this ... Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related ...

Motional

Machine Learning Systems Engineer

Boston, MA · On-site

$144K - $192K/yr

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this ... Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related ...

next page

Showing results 1-20

All JobsPhd Machine Learning JobsPhd Machine Learning Jobs in Boston, MA

Phd Machine Learning information

See Boston, MA salary details

$15

$24

$33

How much do phd machine learning jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for phd machine learning in Boston, MA is $24.79, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.69 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities near Boston, MA are hiring for Phd Machine Learning jobs? Cities near Boston, MA with the most Phd Machine Learning job openings:
Phd Machine Learning jobs near you
Infographic showing various Phd Machine Learning job openings in Boston, MA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $51,569 per year, or $24.8 per hour.

Machine Learning Engineer II / Senior Machine Learning Engineer I, Physical Sciences

Lila Sciences

Cambridge, MA

$114K - $156K/yr

Other

Re-posted 10 days ago

Job description

Your Impact at LILA

This Machine Learning Engineer for the Physical Sciences team focuses on building and operating end-to-end, scalable machine learning workflows that solve a diversity scientific use cases in materials, chemistry and physical sciences. Your work will advance research efforts on state-of-the-art algorithms to build towards scientific superintelligence across today's greatest challenges in physical sciences.

What You'll Be Building

  • Design, implement, and maintain endtoend ML pipelines (data ingestion, feature engineering, training, evaluation, deployment, monitoring).
  • Productionize models and services with robust testing, observability, and documentation in collaboration with cross-functional software teams and build CI/CD workflows and automated evaluations to ensure safe, frequent releases.
  • Collaborate with domain scientists and platform engineers to translate research insights into performant, scalable systems.
  • Contribute to technical design reviews, coding standards, and mentoring of best practices.

What You'll Need to Succeed

  • BS/MS/PhD in Computer Science, Engineering, or a related quantitative field, or equivalent industry experience.
  • Strong Python software engineering fundamentals (testing, packaging, typing); experience with machine learning frameworks (e.g., PyTorch, Huggingface, etc.).
  • Experience deploying ML services to production in cloud-based infrastructure (FastAPI/GRPC, containers, orchestration, cloud infra).
  • Handson experience with model deployment in production systems (LLMs, multimodal models, databases, RAG) with strong debugging and profiling skills.
  • Clear communication and collaboration in crossfunctional settings.

Bonus Points For

  • Exposure to scientific or engineering domains (materials, chemistry, physics) and related data formats/benchmarks.
  • GPU optimization experience (CUDA, Triton, compilation, distributed training).
  • Prior contributions to opensource ML or scientific software.
  • Experience with workflow orchestration, data provenance, or largescale compute environments.

Apply