Senior Staff AI Engineer

Overview

Senior Staff AI Engineer to architect and lead reinforcement learning–driven AI reasoning models and systems that power JazzX AI's enterprise AGI platform, from experimentation and simulation through production deployment.

What you'll do

• Define and drive the end-to-end architecture for reinforcement learning–based systems, including training pipelines, simulation environments, reward shaping, and model serving.
• Apply cutting-edge RL techniques (policy optimization, model-based RL, hierarchical RL, multi-agent RL, etc) to solve complex enterprise problems.
• Design distributed training systems, leverage cloud-native infrastructure, and optimize for performance, reproducibility, and cost-efficiency.
• Provide technical leadership to AI engineers and researchers; mentor junior team members; review designs and code with a focus on scalability, robustness, and clarity.
• Partner with product, data, and platform teams to align RL solutions with strategic business goals and integrate them into production systems.
• Define frameworks for benchmarking, continuous evaluation, and feedback-driven improvements in deployed RL models.
• Ensure RL systems align with ethical AI practices, safety constraints, and regulatory standards for enterprises.

What you'll need

• 10+ years of experience in AI/ML engineering, including at least 5 years specializing in reinforcement learning research and production systems.
• Demonstrated success in designing and deploying large-scale RL architectures in enterprise environments.
• Deep expertise in reinforcement learning algorithms, including on-policy (PPO, A3C) and off-policy (SAC, DDPG) methods, along with hands-on work in simulation frameworks (e.g., OpenAI Gym, Isaac Gym, PettingZoo, MuJoCo).
• Practical experience with multi-agent reinforcement learning (MARL), including coordination strategies for complex environments.
• Strong proficiency in Reinforcement Learning with Verifiable Rewards (RLVR) and GRPO-like policy optimization approaches.
• Experience with test-time compute optimization techniques, including inference-time search, chain-of-thought reasoning, and adaptive computation strategies.
• Proven ability in large language model (LLM) training and fine-tuning, across both supervised and reinforcement learning–driven techniques.
• Advanced software engineering skills in Python, C++, or Java, with deep expertise in ML frameworks such as TensorFlow, PyTorch, JAX, or Ray RLlib.
• Hands-on experience with distributed training infrastructure (Kubernetes, GPU/TPU clusters, and cloud ML platforms).
• Excellent communication, collaboration, and leadership skills, with experience working across multidisciplinary teams.

Nice to have

• PhD in Computer Science, Machine Learning, Robotics, or related field.
• Experience leading enterprise AI adoption and guiding organizational strategy for RL powered systems.
• Contributions to open-source RL frameworks or publications in top-tier conferences (NeurIPS, AISTATS, ICML, ICLR, AAAI).
• Background in safety, alignment, or explainability of RL agents.

Details

• Location: Bangalore.
• Salary range: USD 207,000 to USD 290,000, plus equity options.
• Benefits include health, dental, and vision insurance and flexible working arrangements.