Machine Learning Engineer, Reinforcement Learning

**About Xenonstack** XenonStack is the fastest-growing **Data and AI Foundry for Agentic Systems** , enabling people and organizations to gain **real-time and intelligent business insights** . **We Deliver Innovation Through** - Akira AI – Building Agentic Systems for AI Agents - XenonStack Vision AI – Vision AI Platform - NexaStack AI – Inference AI Infrastructure for Agentic Systems Our mission is to accelerate the world’s transition to **AI + Human Intelligence** , combining reasoning, perception, and action to create **enterprise-ready AI agents** . **THE OPPORTUNITY** We are seeking an **Agentic AI Engineer (Specialized in Reinforcement Learning)** with **2–5 years of experience** in applying RL to enterprise-grade systems. This role involves designing and deploying **adaptive AI agents** that continuously learn, optimize decisions, and evolve in dynamic environments. You’ll work at the intersection of **RL research, agentic orchestration, and real-world enterprise workflows** — building agents that do more than automate, but truly **reason, adapt, and improve over time** . **Job Roles And Responsibilities** **Reinforcement Learning Development** - Design, implement, and train RL algorithms (PPO, A3C, DQN, SAC) for enterprise decision-making tasks. - Develop custom simulation environments to model business processes and operational workflows. - Experiment with reward function design to balance efficiency, accuracy, and long-term value creation. **Agentic AI System Design** - Build production-ready RL-driven agents capable of dynamic decision-making and task orchestration. - Integrate RL models with LLMs, knowledge bases, and external tools for agentic workflows. - Implement multi-agent systems to simulate collaboration, negotiation, and coordination. **Deployment & Optimization** - Deploy RL agents on cloud and hybrid infrastructures (AWS, GCP, Azure). - Optimize training and inference pipelines using distributed computing frameworks (Ray RLlib, Horovod). - Apply model optimization techniques (quantization, ONNX, TensorRT) for scalable deployment. **Evaluation & Monitoring** - Develop pipelines for evaluating agent performance (robustness, reliability, interpretability). - Implement fail-safes, guardrails, and observability for safe enterprise deployment. - Document processes, experiments, and lessons learned for continuous improvement. **Skills Requirements** **Technical Skills** - 2–5 years of hands-on experience with Reinforcement Learning frameworks (Ray RLlib, Stable Baselines, PyTorch RL, TensorFlow Agents). - Strong programming skills in Python; proficiency with PyTorch / TensorFlow. - Experience designing and training RL algorithms (PPO, DQN, A3C, Actor-Critic methods). - Familiarity with simulation environments (Gymnasium, Isaac Gym, Unity ML-Agents, custom simulators). - Experience in reward modeling and optimization for real-world decision-making tasks. - Knowledge of multi-agent systems and collaborative RL is a strong plus. - Familiarity with LLMs + RLHF (Reinforcement Learning with Human Feedback) is desirable. - Exposure to cloud platforms (AWS/GCP/Azure), containers (Docker, Kubernetes), and CI/CD for ML. **Professional Attributes** - Strong analytical and problem-solving mindset. - Ability to balance research depth with practical engineering for production-ready systems. - Collaborative approach, working across AI, data, and platform teams. - Commitment to Responsible AI (bias mitigation, fairness, transparency). **XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT!** At XenonStack, we believe in **shaping the future of intelligent systems** . We foster a **culture of cultivation** built on bold, human-centric leadership principles, where **deep work, simplicity, and adoption** define everything we do. **Our Cultural Values** - Agency – Be self-directed and proactive. - Taste – Sweat the details and build with precision. - Ownership – Take responsibility for outcomes. - Mastery – Commit to continuous learning and growth. - Impatience – Move fast and embrace progress. - Customer Obsession – Always put the customer first. **Our Product Philosophy** - Obsessed with Adoption – Making AI agents accessible and enterprise-ready. - Obsessed with Simplicity – Turning complex RL + agentic challenges into intuitive, reliable systems. Be part of our mission to **reimagine adaptive, enterprise-grade AI agents** with Reinforcement Learning and accelerate the world’s transition to **AI + Human Intelligence** . **WHY SHOULD YOU JOIN US?** - Agentic AI Product Company Build **enterprise-grade AI platforms** powered by Machine Learning, Generative AI, and Agentic Systems. From Vision AI to Inference Infrastructure, you’ll shape products that redefine enterprise AI adoption. - A Fast-Growing Category Leader XenonStack is one of the **fastest-growing Data and AI Foundries** , setting benchmarks in how businesses deploy and scale AI agents with platforms like **Akira AI, NexaStack, and Vision AI** . - Career Mobility & Growth Move between roles and functions — from **AI Engineering to Product Marketing or AgentOps** — and craft a career that grows with your aspirations. - Global Exposure Work with **Fortune 500 enterprises, BFSI leaders, and global innovators** , delivering real-world impact across industries and geographies. - Create Real Impact Contribute from day one. Even junior team members work on **mission-critical product features** that go into production. - Culture of Excellence Our values — **Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession** — empower you to push boundaries and innovate fearlessly. - Responsible AI First Join a company that prioritizes **trustworthy, explainable, and compliant AI** . You’ll contribute to **Responsible AI frameworks** , ensuring our agentic systems are not just powerful, but also ethical and reliable.