... vision, reinforcement learning, LLM applications and human computer interaction solutions for a ... parts, robotic perception and prognostics and health management. We conduct basic and applied ...
... vision, reinforcement learning, LLM applications and human computer interaction solutions for a ... parts, robotic perception and prognostics and health management. We conduct basic and applied ...
... vision, reinforcement learning, LLM applications and human computer interaction solutions for a ... parts, robotic perception and prognostics and health management. We conduct basic and applied ...
... vision, reinforcement learning, LLM applications and human computer interaction solutions for a ... parts, robotic perception and prognostics and health management. We conduct basic and applied ...
Reinforcement Learning Robotics information
What is reinforcement learning in robotics?
Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.
What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?
One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.
What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?
To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.
What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?
| Aspect | Reinforcement Learning Robotics | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Degree in Robotics, Computer Science, or related fields; knowledge of reinforcement learning | Degree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms |
| Work Environment | Robotics labs, manufacturing, autonomous systems | Tech companies, data-driven projects, software development |
| Industry Usage | Autonomous robots, industrial automation, research | Data analysis, predictive modeling, AI applications |
Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.
What are popular job titles related to Reinforcement Learning Robotics jobs in Connecticut?
For Reinforcement Learning Robotics jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Robotics jobs in Connecticut look for?
The top searched job categories for Reinforcement Learning Robotics jobs in Connecticut are:
- Senior Deep Learning Research
- Hourly Remote Machine Learning
- Machine Learning Research Intern
- Gpu Engineer Salary
- Junior Machine Learning
- Artificial Intelligence Machine Learning Engineer
- Senior Meta Machine Learning
- Flexible Teen Robotics Engineer
- Remote Machine Learning Robotics
- No Experience Nvidia Machine Learning
What cities in Connecticut are hiring for Reinforcement Learning Robotics jobs?
Cities in Connecticut with the most Reinforcement Learning Robotics job openings:
Agentic AI Researcher (Hybrid)
East Hartford, CT • On-site
Raytheon Technologies
• Guided Missile and Space Vehicle Manufacturing • 10K+ employees10,000+ employees
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 22 days ago
RTX rating
8.2
Based on 86 frontline employees who took The Breakroom Quiz
Job description
Date Posted:
2026-08-20
Country:
United States of America
Location:
US-CT-EAST HARTFORD-RTRC K ~ 411 Silver Ln ~ RTRC K
Position Role Type:
Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
This job requires a U.S. Person. A U.S. Person is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or who is a protected individual as defined by 8 U.S.C. 1324b(a)(3). U.S. citizens, U.S. nationals, U.S. permanent residents, or individuals granted refugee or asylee status in the U.S. are considered U.S. persons. For a complete definition of "U.S. Person" go here: https://www.ecfr.gov/current/title-22/chapter-I/subchapter-M/part-120/subpart-C/section-120.62
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required
At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.
The following position is to join our RTX Research Center team:
Role Overview:
Seeking a motivated and curious candidate for an Agentic AI Researcher position in the Advanced Learning and Analytics team, part of the AI Discipline.
The Advanced Learning and Analytics team researches and develops machine learning, computer vision, reinforcement learning, LLM applications and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomous flight, material discovery and design, automated visual inspection of parts, robotic perception and prognostics and health management. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners and subject matter experts collaborate and exchange experience.
This role focuses on creating grounded, explainable and verifiable AI systems capable of operating in complex high-stakes environments such as autonomous systems, command and control, decision support and safety critical domains.
What You Will Do:
What You Will Learn:
Qualifications You Must Have:
Qualifications We Prefer:
What We Offer: Whether you're just starting out on your career journey or are an experienced professional, we offer a robust total rewards package with compensation; healthcare, wellness, retirement and work/life benefits; career development and recognition programs. Some of the benefits we offer include parental (including paternal) leave, flexible work schedules, achievement awards, educational assistance and child/adult backup care.
Learn More & Apply Now!
Work Location: Hybrid - East Hartford, CT
Please consider the following role type definition as you apply for this role:
Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.
The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.
Privacy Policy and Terms:
Click on this link to read the Policy and Terms
2026-08-20
Country:
United States of America
Location:
US-CT-EAST HARTFORD-RTRC K ~ 411 Silver Ln ~ RTRC K
Position Role Type:
Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
This job requires a U.S. Person. A U.S. Person is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or who is a protected individual as defined by 8 U.S.C. 1324b(a)(3). U.S. citizens, U.S. nationals, U.S. permanent residents, or individuals granted refugee or asylee status in the U.S. are considered U.S. persons. For a complete definition of "U.S. Person" go here: https://www.ecfr.gov/current/title-22/chapter-I/subchapter-M/part-120/subpart-C/section-120.62
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required
At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.
The following position is to join our RTX Research Center team:
Role Overview:
Seeking a motivated and curious candidate for an Agentic AI Researcher position in the Advanced Learning and Analytics team, part of the AI Discipline.
The Advanced Learning and Analytics team researches and develops machine learning, computer vision, reinforcement learning, LLM applications and human computer interaction solutions for a variety of high impact real world problems in the aerospace, manufacturing and defense industries. Examples include autonomous flight, material discovery and design, automated visual inspection of parts, robotic perception and prognostics and health management. We conduct basic and applied research in a stimulating multi-disciplinary environment where scientists, engineers, practitioners and subject matter experts collaborate and exchange experience.
This role focuses on creating grounded, explainable and verifiable AI systems capable of operating in complex high-stakes environments such as autonomous systems, command and control, decision support and safety critical domains.
What You Will Do:
- Design and build the next-generation agentic AI systems that combine the strengths of machine learning (LLMs, RL, deep learning) with symbolic reasoning, knowledge graphs and formal methods.
- Research, design and implement novel ML approaches for multi-modal data.
- Develop algorithms, publish and present your findings to both internal and external stakeholders
- Initiate, lead, and develop capabilities by seeking funding opportunities through internal and external R&D.
What You Will Learn:
- You will learn to collaborate and participate in a world class multi-disciplinary research environment working. Learn about challenges and help develop AI solutions in critical domains of aerospace and defense.
Qualifications You Must Have:
- Typically requires: A University Degree In Computer Science or equivalent experience and minimum 5 years prior relevant experience, or An Advanced Degree in a related field and minimum 3 years experience
- Minimum 3 years of hands-on experience in various ML techniques, off-the-shelf packages and development environments.
- Experience with building ML, LLMs and agentic systems and has a deep understanding of various ML and agentic frameworks like Pytorch, LangGraph, AutoGen
- Ability to understand and use details of an engineering problem statement, formulate it as an ML problem and identify candidate ML approaches.
- Research experience in synthesizing and combining multiple ML approaches to address novel engineering problems.
Qualifications We Prefer:
- Ph.D. in Computer Science or a related field
- 5+ years of professional ML experience with 2+ developing agentic solutions
- 5+ years of experience applying and adapting ML approaches from academic literature to real world problems.
- Experience with finetuning LLMs for pushing the reasoning capabilities
- Prior experience in Aerospace and Defense applications
- Published work in flagship conferences- NeurIPS, ICML, ICLR
What We Offer: Whether you're just starting out on your career journey or are an experienced professional, we offer a robust total rewards package with compensation; healthcare, wellness, retirement and work/life benefits; career development and recognition programs. Some of the benefits we offer include parental (including paternal) leave, flexible work schedules, achievement awards, educational assistance and child/adult backup care.
Learn More & Apply Now!
Work Location: Hybrid - East Hartford, CT
Please consider the following role type definition as you apply for this role:
Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.
As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote.
The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.
Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.
This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply.
RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.
RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.
Privacy Policy and Terms:
Click on this link to read the Policy and Terms
About RTX
Sourced by ZipRecruiter
Industry
Guided missile and space vehicle manufacturing, it services, aerospace product and parts manufacturing and engineering professional services
Company size
10,000+ Employees
Headquarters location
Waltham, MA, US