4 hours ago
Bengaluru, IndiaStaff+
Base Salary
$207k - $290k/yr
Responsibilities
- Define end-to-end architecture for reinforcement-learning systems, including training pipelines, simulation environments, reward shaping, and model serving.
- Apply policy optimization, model-based, hierarchical, and multi-agent reinforcement-learning techniques to complex enterprise problems.
- Design distributed training systems and cloud-native infrastructure optimized for performance, reproducibility, scalability, and cost efficiency.
- Provide technical leadership and mentorship to AI engineers and researchers, including design and code reviews.
- Partner with product, data, platform, and research teams to integrate RL solutions into production systems.
- Create benchmarking, continuous evaluation, and feedback-driven improvement frameworks for deployed RL models.
- Ensure RL systems meet ethical AI, safety, explainability, governance, and enterprise regulatory standards.
- Explore novel RL techniques and bridge research advances into reliable enterprise production solutions.
Requirements
- At least 10 years of AI/ML engineering experience, including at least 5 years specializing in reinforcement-learning research and production systems.
- Demonstrated success designing and deploying large-scale RL architectures in enterprise environments.
- Deep expertise in RL algorithms, including PPO, A3C, SAC, and DDPG, with hands-on experience in simulation frameworks.
- Practical experience with multi-agent reinforcement learning and coordination strategies for complex environments.
- Strong proficiency with Reinforcement Learning with Verifiable Rewards, GRPO-like policy optimization, and test-time compute optimization techniques.
- Experience with inference-time search, chain-of-thought reasoning, and adaptive computation strategies.
- Experience training and fine-tuning large language models using supervised and reinforcement-learning techniques.
- Advanced software engineering skills in Python, C++, or Java.
- Deep expertise in TensorFlow, PyTorch, JAX, or Ray RLlib.
- Hands-on experience with distributed training infrastructure, Kubernetes, GPU/TPU clusters, and cloud ML platforms.
- Strong communication, collaboration, and leadership skills across multidisciplinary teams.
- Preferred: PhD in Computer Science, Machine Learning, Robotics, or a related field.
- Preferred: experience leading enterprise AI adoption and organizational strategy for RL-powered systems.
- Preferred: contributions to open-source RL frameworks or publications at NeurIPS, AISTATS, ICML, ICLR, or AAAI.
- Preferred: background in safety, alignment, or explainability of RL agents.
Benefits
- Competitive base salary ranging from USD 207,000 to USD 290,000, plus equity options.
- Health, dental, and vision insurance.
- Flexible working arrangements.
- The role is based at the company headquarters in Los Altos, California.
Tech Stack
Categories
AI ResearchML Engineering
About JazzX AI
JazzX AI builds AI-native digital workers that execute governed, explainable workflows for enterprises, starting with lending and due-diligence processes. The company offers enterprise software and AI infrastructure to capture expert judgment, automate decisions, and run complex, regulated operations at scale. Founded in 2024 and privately held, it is based in California and backed by SAI Group.