Machine Learning Engineer, Reinforcement Learning

XenonStack Moments; San Martin Cp3 Hualtaco I; Presencial; PEN 305.000 - 407.000; Jornada completa

Descripción de la vacante

XenonStack is a leader in Data and AI Foundry, building agentic systems for enterprise use. We seek a Machine Learning Engineer, Reinforcement Learning with 2-5 years of hands-on experience to design and deploy adaptive AI agents that learn and improve in dynamic environments.

You'll work at the intersection of RL research and production, integrating RL with LLMs, orchestrating agents, and delivering scalable, observable solutions on cloud and hybrid platforms.

Formación

• 2-5 years of hands-on RL experience in enterprise-grade systems.
• Strong Python programming with PyTorch or TensorFlow.
• Experience designing and training RL algorithms (PPO, DQN, A3C).
• Familiarity with simulation environments and custom environments.
• Experience integrating RL with LLMs and external tools.
• Understanding of responsible AI, safety, and guardrails.

Responsabilidades

• Design, implement, and train RL algorithms for enterprise tasks.
• Develop custom simulators to model business processes.
• Integrate RL models with LLMs and external tools.
• Deploy RL agents on cloud and hybrid infrastructure.
• Monitor, evaluate, and iterate on agent performance.

Conocimientos

Reinforcement Learning

Ray RLlib

PyTorch

Python

TensorFlow

RLHF / LLMs

Simulation Environments

Distributed Computing

Docker & Kubernetes

Cloud Platforms

Herramientas

Gymnasium

Isaac Gym

Unity ML-Agents

Docker

Kubernetes

Ray RLlib

TensorFlow

PyTorch

CI/CD for ML

Descripción del empleo

About Xenonstack

XenonStack is a Data and AI Foundry for Agentic Systems, enabling enterprises to design, deploy, operate, and scale intelligent agents across digital and physical environments.

About Xenonstack

XenonStack is a Data and AI Foundry for Agentic Systems, enabling enterprises to design, deploy, operate, and scale intelligent agents across digital and physical environments.

We Build Enterprise-grade Platforms Across The Agentic Stack

• Akira AI - Reasoning and agent orchestration. Turn models into collaborative, policy-governed agents that learn and act together.
• ElixirData - Agentic analytics intelligence. Explainable, decision-centric analytics for measurable business outcomes.
• NexaStack - Agentic infrastructure automation. Secure, compliant AI deployment across cloud, edge, and on-prem.
• MetaSecure - Trust, compliance and defense. Continuous assurance with AI-BOMs, risk scoring, and agentic security.

Our mission is to accelerate the world’s transition to AI + Human Intelligence by making agentic systems reliable, responsible, and enterprise-ready.

THE OPPORTUNITY

We are seeking an Machine Learning Engineer, Reinforcement Learning (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.