Hands-on experience in working with autonomous systems, artificial intelligence, deep/reinforcement/machine learning, robotics, dynamics and controls, flight test and evaluation, modeling ...
Hands-on experience in working with autonomous systems, artificial intelligence, deep/reinforcement/machine learning, robotics, dynamics and controls, flight test and evaluation, modeling ...
Hands-on experience in working with autonomous systems, artificial intelligence, deep/reinforcement/machine learning, robotics, dynamics and controls, flight test and evaluation, modeling ...
Hands-on experience in working with autonomous systems, artificial intelligence, deep/reinforcement/machine learning, robotics, dynamics and controls, flight test and evaluation, modeling ...
... 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 ...
Agentic AI Researcher
East Hartford, CT · On-site
... 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 ...
Agentic AI Researcher
East Hartford, CT · On-site
... 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 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 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 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:
- Robot
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What cities in Connecticut are hiring for Reinforcement Learning Robotics jobs? Cities in Connecticut with the most Reinforcement Learning Robotics job openings:
Research Scientist - Autonomous Collaborative Systems
East Hartford, CT • On-site
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 9 days ago
Job description
Date Posted:
2026-07-08
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
RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses - Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity. The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA.
Position Overview:
RTX Technology Research Center (RTRC) has a newly created position of Research Scientist in Autonomous Collaborative Systems (ACS). In this role, you will join the ACS team under the Artificial Intelligence (AI) discipline at RTRC. The team is engaged in a wide variety of research areas including computer vision, decision making, trustworthy and explainable AI and human-machine symbiosis for a variety of high impact real world problems in the aerospace, manufacturing, and defense industries. Examples of relevant problems include multi-agent coordination, self-functioning systems of systems, cybersecurity, automated visual inspection of parts, and robotic perception and manipulation.
What You Will Do:
Qualifications You Must Have:
Qualifications We Prefer:
Work Location
This is a hybrid role, 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 107,500 USD - 204,500 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
2026-07-08
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
RTX Corporation is an Aerospace and Defense company that provides advanced systems and services for commercial, military and government customers worldwide. It comprises three industry-leading businesses - Collins Aerospace Systems, Pratt & Whitney, and Raytheon. Its 185,000 employees enable the company to operate at the edge of known science as they imagine and deliver solutions that push the boundaries in quantum physics, electric propulsion, directed energy, hypersonics, avionics and cybersecurity. The company, formed in 2020 through the combination of Raytheon Company and the United Technologies Corporation aerospace businesses, is headquartered in Arlington, VA.
Position Overview:
RTX Technology Research Center (RTRC) has a newly created position of Research Scientist in Autonomous Collaborative Systems (ACS). In this role, you will join the ACS team under the Artificial Intelligence (AI) discipline at RTRC. The team is engaged in a wide variety of research areas including computer vision, decision making, trustworthy and explainable AI and human-machine symbiosis for a variety of high impact real world problems in the aerospace, manufacturing, and defense industries. Examples of relevant problems include multi-agent coordination, self-functioning systems of systems, cybersecurity, automated visual inspection of parts, and robotic perception and manipulation.
What You Will Do:
- Designing and developing algorithms for perception, decision-making, human-machine collaboration, networked and teamed systems, and next generation autonomous platforms.
- Prototyping and simulating autonomous systems by writing code, developing software (simulation and visualization), interfacing software/hardware, and supporting real-time demonstrations of autonomy in live, virtual, and simulation test environments.
- Leading and supporting externally and internally sponsored programs, writing external and internal research proposals.
- Building relationships to support partnership with leading, worldwide institutions (university, government agencies, national labs, and professional organizations) and meet organizational objectives.
- Disseminating research results through reports, conference proceedings, presentations, and technical papers for archival journals.
- The ideal candidate will possess a strong foundation in AI and Autonomy, demonstrated by a track record of innovation through patents, contributions to research, and/or publications in prestigious venues. Relevant conferences include NeurIPS (Conference on Neural Information Processing Systems), CVPR (Computer Vision and Pattern Recognition Conference), ICRA (International Conference on Robotics and Automation), IROS (International Conference on Intelligent Robots and Systems), RSS (Robotics: Science and Systems), and AAAI (Association for the Advancement of Artificial Intelligence), among other leading research forums.
Qualifications You Must Have:
- Typically requires a University Degree or equivalent experience and minimum 8 years prior relevant experience, or an Advanced Degree in a related field and minimum 5 years experience
- PhD Required
- Hands-on experience in working with autonomous systems, artificial intelligence, deep/reinforcement/machine learning, robotics, dynamics and controls, flight test and evaluation, modeling & simulation, data science, and statistical analysis.
- Experience applying AI based perception and/or Reinforcement Learning techniques to solve real world problems
Qualifications We Prefer:
- Experience using a modern software development environment including automated testing, continuous integration, and deployment, and "DevSecOps" environments.
- Experience setting technical direction from initiation to execution of projects and managing technical deliverables for a small team.
- Experience with PyTorch/TensorFlow, ROS, MATLAB; Real-time control prototyping and Software/Hardware-in-the-Loop testing
- Strong analytical, problem-solving, written/verbal communication, and interpersonal skills with track record of teamwork, adaptability, innovation, and initiative.
- Clear and effective communication with all levels of management, business development, researchers, and customers.
- Ability to work independently with limited direction and in multidisciplinary environment.
- Languages/Frameworks: Python, C++; cloud computing, and configuration management.
- Broad awareness of advancements in intelligent autonomous systems
Work Location
This is a hybrid role, 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 107,500 USD - 204,500 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 Raytheon Technologies
Sourced by ZipRecruiter
Industry
Aerospace product and parts manufacturing and it services
Company size
10,000+ Employees
Headquarters location
Waltham, MA, US