Manager Remote Machine Learning Engineer Jobs in Houston, TX

Sperry Drilling delivers industry-leading Measurement-While-Drilling (MWD), Logging-While-Drilling (LWD), and Rotary Steerable System (RSS) technologies that help operators drill safer, faster, and more precisely. Through advanced downhole tools, real-time data acquisition, and reliability-driven engineering, Sperry enables customers to maximize well placement, efficiency, and reservoir understanding in every drilling environment.

The Controls & Modeling Engineer advances research and development of next-generation automation, controls, robotics, and intelligent systems technologies within the Advanced Controls COE.

This role focus on rigorous application of advanced control theory, dynamic modeling, estimation, optimization, machine learning, and agentic AI to high-value engineering problems.

Work spans early-stage concept generation, algorithm development, simulation and validation, prototype implementation, and transition of emerging technologies into deployable workflows and systems.

This position contributes to strategic R&D initiatives with direct commercial relevance. Scope includes development of physics-based and data-driven methods for automation, operational decision support, autonomous and semi-autonomous systems, and model-based performance improvement. Close collaboration with multidisciplinary teams across engineering, software, digital, and operations.

Key Responsibilities

• Develop and evaluate agentic AI systems that combine reasoning, tools, data, and simulation assets to enable advanced technical analysis, automation, and human-in-the-loop decision making. 
• Integrate large language models (LLMs), retrieval-augmented systems, and AI agents with controls, modeling, and optimization frameworks. 
• Develop machine learning, data analytics, and hybrid physics-AI approaches to improve system performance, automation, and operational efficiency. 
• Develop software tools, workflows, orchestration pipelines, and visualization capabilities to support AI-enabled engineering and operations. 
• Conduct research and development in advanced controls, robotics, dynamic modeling, and automation for complex engineering systems. 
• Design & apply advanced control techniques including adaptive, nonlinear, robust, optimal, and model predictive control (MPC). 
• Develop and validate dynamic models, simulations, and system identification methodologies. 
• Collaborate with multidisciplinary teams across engineering, software, data science, and operations. 
• Contribute to technical innovation through patents, publications, conferences, and internal programs. 

Required

• PhD or equivalent experience in a relevant engineering or scientific discipline with emphasis on controls, dynamic systems, automation, machine learning, or intelligent systems; or equivalent R&D experience. 
• Experience with agentic AI, LLM-based workflows, orchestration frameworks, or tool-using AI agents applied to scientific, industrial, or engineering use cases. 
• Deep knowledge of control theory, including modern control, optimal control, Model Predictive Control (MPC), and system dynamics. 
• Knowledge of robotics, mechatronics, high‑DoF systems, path planning, and dynamic modeling. 
• Strong technical communication and collaboration skills. 

Preferred

• Ability to build data pipelines, workflows, and analytical tools for AI/ML tool chain which includes data cleaning, feature extraction, optimization, and insight generation. 
• Strong programming skills in MATLAB, Python, C/C++, C#, Java, or similar languages. 
• Create dashboards and use data visualization tools such as Python, or JavaScript Typescript frameworks. 
• Ability to design, analyze, and troubleshoot control systems, sensors, actuators, pumps, VFDs, and automation hardware. 
• Strong capability to read and interpret electrical schematics, mechanical drawings, P&IDs, flow charts, and cause‑and‑effect diagrams.  

Candidates exceeding minimum requirements may be considered for higher-level positions based on experience, additional qualifications, and business needs. Career progression ranges Controls & Modeling Engineer Senior to Controls & Modeling Engineer Principal. 

At Halliburton, we’re committed to supporting you and your family with a comprehensive and affordable benefits package that covers your physical, emotional, financial, and parental needs — now and in the future. When you join our team, you’ll gain access to a wide range of programs designed to help you thrive at work and at home.

Click here to review a summary of the benefits available once you join.

Advanced Control Systems | Control Theory & System Identification | Robotics & Autonomous Systems | High DoF Systems & Path Planning | Modeling & Simulation | Control + Machine Learning | Data Analytics + Engineering | Neural Networks & Bayesian Methods | MATLAB/Simulink & Python | Dynamic Systems & Optimization | Robotics + Control | Theory + Practical Deployment | Field Implementation Experience | Cross-Functional Collaboration | Innovation & Technology Development