Your role on our team
Pioneer the application of reinforcement learning (RL) and sequential decision-making to high-impact challenges across ExxonMobil's upstream, downstream, and commercial operations.
Collaborate with engineers, scientists, and business stakeholders to turn complex operational and planning problems into deployable, production-grade RL solutions.
Advance the organization's capabilities in reinforcement learning, decision optimization, and autonomous control as part of the Modeling, Optimization, and Data Science (MODS) team.
What you will do
- Design, develop, and deploy reinforcement learning solutions for real-world energy applications such as production optimization, process control, supply chain scheduling, drilling optimization, and resource allocation.
- Formulate sequential decision problems by defining state spaces, action spaces, reward structures, transition dynamics, and operational constraints with domain experts.
- Develop RL agents using model-free methods (e.g., PPO, SAC, TD3, DQN where appropriate) and model-based approaches, selecting methods based on problem requirements, safety, and data availability.
- Build and use simulation environments and digital twins for offline training, policy evaluation, and validation before real-world deployment.
- Apply safe and constrained RL techniques to ensure agents operate within operational and safety limits.
- Integrate RL solutions with existing optimization, simulation, and control systems across real-time and planning use cases.
- Partner with data scientists and ML engineers to operationalize solutions, including training pipelines, monitoring, retraining, and performance tracking.
- Benchmark RL against traditional methods such as LP, MIP, heuristic search, MPC, and stochastic optimization to identify best-fit approaches.
- Stay current with advances in offline RL, safe RL, multi-agent RL, hierarchical RL, and model-based RL.
- Share knowledge, publish findings where appropriate, and mentor peers on RL best practices.
About you
Desired Skills:
- Experienced AI/ML professional with strong expertise in reinforcement learning, sequential decision-making, optimization, and real-world deployment.
- 5+ years of experience in AI/ML, optimization, or related fields, including at least 2 years in reinforcement learning, sequential decision-making, or optimal control.
- Master's or PhD in Computer Science, Machine Learning, Operations Research, Control Theory, Robotics, Applied Mathematics, Engineering, or a related quantitative field.
- Deep understanding of RL fundamentals, including MDPs, dynamic programming, temporal-difference learning, policy gradients, and actor-critic methods.
- Proven experience building RL systems end-to-end, from environment and reward design through training, evaluation, and deployment.
- Experience with simulation environments, digital twins, or system models.
- Strong background in statistics, probability, optimization, control theory, and algorithm design.
- Proficiency in Python, PyTorch and/or TensorFlow, plus RL tools such as Stable Baselines3, RLlib, and Gymnasium.
- Strong communication and collaboration skills, including the ability to explain technical concepts to non-technical stakeholders.
Preferred Skills:
- Experience applying RL or decision optimization in industrial domains such as process control, robotics, autonomous systems, supply chain, energy systems, or operations research.
- Familiarity with offline (batch) RL, safe RL, and multi-agent RL.
- Knowledge of model-based RL, MPC, and hybrid RL-control approaches.
- Understanding of classical optimization methods and how RL complements them.
- Experience with physics-informed or hybrid mechanistic/ML modeling and domain-informed reward or constraint design.
- Familiarity with platforms such as Azure ML, Azure OpenAI, Databricks, and MLOps tools such as MLflow or Weights & Biases.
- Experience in the energy industry or other asset-intensive, safety-critical sectors.
Your benefits
An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life.
We offer you:
- Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in retirement for the rest of your life.
- Savings Plan: You can contribute between 6% and 20% of your pay and are encouraged to enroll right away. If you contribute at least 6% to your savings plan, the Company will contribute a 7% match.
- Workplace Flexibility: We have several programs such as "Flex your Day", providing ad-hoc flexibility around when and where you work, as well as longer-term programs such as leaves of absence and part-time work.
- Comprehensive medical, dental, and vision plans.
- Culture of Health: Programs and resources to support your wellbeing.
- Employee Health Advisory Program: Provides co