Machine Learning Engineer, Reinforcement Learning

XenonStack Moments; Vallecito 15-8 Hualtaco I; Presencial; PEN 100.000 - 180.000; Jornada completa

Descripción de la vacante

XenonStack is seeking a Machine Learning Engineer specialized in Reinforcement Learning to design, train, and deploy adaptive AI agents for enterprise environments. You will work at the intersection of RL research, agentic orchestration, and real-world workflows, building agents that learn and improve over time.

The role emphasizes production-ready systems, integration with LLMs, simulation environments, and scalable deployment across cloud and on-prem infrastructures.

Formación

• 2-5 years hands-on Reinforcement Learning experience in enterprise settings.
• Experience designing and training RL algorithms (PPO, A3C, DQN, SAC).
• Experience integrating RL with LLMs and external tools for agentic workflows.
• Experience deploying RL agents on cloud platforms (AWS/GCP/Azure) and using Docker/Kubernetes.
• Experience with simulation environments and custom simulators.
• Strong Python programming skills with PyTorch/TensorFlow.

Responsabilidades

• Design, implement, and train RL algorithms for enterprise decision-making tasks.
• Develop production-ready RL-driven agents capable of dynamic decision-making and task orchestration.
• Deploy RL agents on cloud/hybrid infrastructures and optimize training/inference pipelines.
• Evaluate agent performance, robustness, and interpretability; document experiments and lessons learned.

Conocimientos

Reinforcement Learning

Python programming

Ray RLlib

Stable Baselines

PyTorch

TensorFlow

RL algorithms design

Simulation environments

LLMs + RLHF

Cloud platforms

Docker/Kubernetes

CI/CD for ML

Multi-agent systems

Herramientas

Gymnasium

Unity ML-Agents

Docker

Kubernetes

Ray RLlib

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.

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.