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Postdoctoral In Reinforcement Learning Jobs in Massachusetts

Klaviyo

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

Preferred : • Trained ML models in the past and deployed them in production systems to generate impact to businesses. • Experience in reinforcement learning. Company : Klaviyo is an automation ...

Klaviyo

Senior AI Engineer - Customer Agent

Boston, MA · On-site

$113K - $155K/yr

Preferred : • Trained ML models in the past and deployed them in production systems to generate impact to businesses. • Experience in reinforcement learning. Company : Klaviyo is an automation ...

Klaviyo

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

Preferred : • Trained ML models in the past and deployed them in production systems to generate impact to businesses. • Experience in reinforcement learning. Company : Klaviyo is an automation ...

YO AI Labs

Machine Learning Engineer - Remote

Boston, MA · Remote

$80 - $120/hr

Create reinforcement learning environments for software engineering tasks. * Design tasks involving ... Strong proficiency in Python 3, Java, Rust, C++, or TypeScript . * Strong understanding of ...

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Postdoctoral In Reinforcement Learning information

What is a postdoctoral researcher in reinforcement learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in reinforcement learning?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are popular job titles related to Postdoctoral In Reinforcement Learning jobs in Massachusetts?

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Cities in Massachusetts with the most Postdoctoral In Reinforcement Learning job openings:

Postdoctoral In Reinforcement Learning jobs near you
Infographic showing various Postdoctoral In Reinforcement Learning job openings in Massachusetts as of June 2026, with employment types broken down into 47% Full Time, 38% Part Time, 5% Temporary, 5% Contract, and 5% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

Research Scientist, Reinforcement Learning

Cambridge, MA • On-site

Basis Research Institute
See more jobs at Basis Research Instituteexternal

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Job Summary:
Basis Research Institute is a nonprofit applied AI research organization focused on understanding and building intelligence. The Research Scientist in Reinforcement Learning will lead efforts to develop new methods and algorithms for reinforcement learning and planning, while also contributing to collaborative research projects and mentoring junior team members.
Responsibilities:
• Conduct independent and collaborative research focused on the MARA project.
• Develop new methods and algorithms for reinforcement learning, planning, and decision-making in AI systems.
• Apply these methods to concrete challenges such as AutumnBench, physical and simulated robotics environments, and other domains.
• Disseminate research findings through academic publications and presentations at leading conferences.
• Provide mentorship to junior team members and contribute to the scientific discourse through seminars, workshops, and collaborative projects.
• Develop and maintain open-source software
• (Optionally) Publish and present findings in journals and conferences
• Contribute to the culture and direction of Basis
Qualifications:
Required:
• Researchers holding a PhD in computer science, artificial intelligence, machine learning, cognitive science, or related fields.
• Strong background in reinforcement learning, planning, MDPs, optimal control, and sequential decision making.
• Individuals with a demonstrated track record in scientific research, evidenced through publications, technical reports, or impactful software projects.
• Excited about solving real world problems and having positive societal impact.
Preferred:
• Experience in developing AI systems that combine neural and symbolic methods is highly valued.
• Interest in foundational AI research and its applications to modeling, abstraction, and reasoning.
• Exceptional candidates who may not meet all of the following criteria are still encouraged to apply.
Company:
Basis is a nonprofit applied research organization with two mutually reinforcing goals. The first is to understand and build intelligence. Founded in 2022, the company is headquartered in New York, USA, with a team of 11-50 employees. The company is currently Early Stage.

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