5 months ago
Base Salary
$207k - $290k/yr
Responsibilities
- Define and drive end-to-end architectures for reinforcement-learning systems, including training pipelines, simulation environments, reward shaping, and model serving.
- Apply advanced reinforcement-learning techniques to complex enterprise problems, including policy optimization, model-based RL, hierarchical RL, and multi-agent RL.
- Design distributed training systems and cloud-native infrastructure optimized for performance, reproducibility, and cost efficiency.
- Provide technical leadership, mentor AI engineers and researchers, and review designs and code for scalability and robustness.
- Partner with product, data, platform, and research teams to integrate RL solutions into production systems.
- Define benchmarking, continuous evaluation, monitoring, and feedback-driven improvement frameworks for deployed RL models.
- Ensure RL systems meet ethical AI, safety, explainability, governance, and regulatory standards.
Requirements
- 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, DDPG, RLVR, and GRPO-like policy optimization approaches.
- Hands-on experience with simulation frameworks such as OpenAI Gym, Isaac Gym, PettingZoo, or MuJoCo, and with multi-agent reinforcement learning.
- Experience with test-time compute optimization, 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, with deep expertise in 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 across multidisciplinary teams.
- Preferred qualifications include a PhD in Computer Science, Machine Learning, Robotics, or a related field; enterprise AI adoption leadership; open-source or top-tier conference contributions; and experience with safety, alignment, or explainability of RL agents.
Benefits
- Competitive base salary of USD 207,000 to USD 290,000 plus equity options.
- Health, dental, and vision insurance.
- Flexible working arrangements.
- Opportunity to build foundational enterprise AGI and AI systems with real-world impact.
- Headquartered in Los Altos, California.
Tech Stack
Categories
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.