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AI Research Engineer - Reinforcement Learning
Location
India
JobType
full-time
About the job
This job is sourced from a job board
Overview
About the role
Jobgether
Website:
jobgether.com
Job details:
This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI Research Engineer - Reinforcement Learning in India.
This role sits at the forefront of applied AI research, focusing on advancing reinforcement learning systems that power next-generation intelligent models. You will design and optimize algorithms that improve decision-making, adaptability, and performance across complex, real-world environments. Working in a highly research-driven and experimentation-heavy setting, you will contribute to both foundational RL innovations and production-grade implementations. The position spans work on efficient models for constrained hardware as well as large-scale multimodal systems integrating text, image, and audio. You will play a key role in building simulation environments, refining training pipelines, and enhancing policy performance. This is an opportunity to directly shape cutting-edge AI systems deployed at global scale.
Accountabilities
Design and implement advanced reinforcement learning algorithms to improve decision-making, policy optimization, and system performance across simulated and real-world environments
Run controlled experiments, track performance metrics, evaluate outcomes against benchmarks, and iterate on model improvements through empirical analysis
Develop and curate high-quality simulation environments and training datasets aligned with domain-specific requirements and learning objectives
Debug and optimize RL pipelines, addressing challenges such as exploration strategy, reward stability, sample efficiency, and training convergence
Collaborate with engineering and research teams to integrate RL agents into production systems and ensure measurable real-world performance gains
Define evaluation frameworks and continuously monitor deployed systems to support robustness, scalability, and domain adaptation
Requirements
Advanced degree in Computer Science, Machine Learning, or related field; PhD preferred with strong academic research background and publications in top-tier conferences
Proven experience running large-scale reinforcement learning projects, including modern online RL techniques such as policy optimization methods and actor-critic frameworks
Deep understanding of reinforcement learning theory and practice, including policy gradients, exploration-exploitation trade-offs, and optimization strategies for stability and efficiency
Strong hands-on expertise with PyTorch and RL frameworks, including building full pipelines from simulation to training and deployment
Demonstrated ability to solve complex RL challenges such as sample inefficiency, reward noise, and training instability through empirical and algorithmic innovation
Strong analytical mindset with ability to design robust experiments, interpret results, and continuously improve model performance
Benefits
Fully remote work environment with global team collaboration
Opportunity to work on cutting-edge AI and reinforcement learning research at scale
High-impact role influencing production-level AI systems and real-world applications
Competitive compensation aligned with experience and expertise
Exposure to advanced research, multimodal AI systems, and state-of-the-art infrastructure
Flexible working culture supporting autonomy and innovation
How Jobgether Works
We use an
AI-powered matching process
to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice:
By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Click on Apply to know more.
Skills
adaptability
Artificial Intelligence
machine learning
team collaboration
Pytorch
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