Process Control Engineer

Streamline Innovations•San Antonio, TX

13h

About The Position

We are seeking a Process Control Engineer with a strong foundation in chemical process systems and control theory to support advanced process optimization, automation projects, and plant performance improvement initiatives. The ideal candidate combines a deep theoretical understanding of traditional process modeling, prediction, and control with data-driven techniques. This role bridges classical process control engineering and modern digital transformation - requiring both strong analytical ability and creativity in applying control principles to complex chemical systems.

Requirements

M.S. or Ph.D. in Chemical or Mechanical Engineering with emphasis in Process Systems Engineering, Control, or Dynamics.
or
B.S. in Chemical or Mechanical Engineering with a demonstrated portfolio of real-world results in the responsibility areas.
3+ years of experience in a process engineering or control engineering role within the chemical or energy industries (industrial internships or research experience acceptable for advanced degree holders).
Strong proficiency in process control fundamentals: dynamic modeling, process identification, process optimization
Familiarity with MATLAB/Simulink, Aspen DMC, Python, or similar tools for modeling and control system analysis.
Understanding of process safety systems, alarm management, and ISA standards (ISA 18.2, ISA 84, ISA 101).
Knowledge of chemical process unit operations (distillation, heat exchange, reaction, separation, and fluid transport).
Strong analytical and systems-thinking mindset.
Ability to translate theoretical models into practical industrial control solutions.
Effective communication of complex technical topics to multidisciplinary teams.
Self-starter comfortable with both design and operations environments.
Prolonged periods sitting at a desk and working on a computer.
Must be able to lift to 15lbs pounds at times.

Nice To Haves

Model predictive control (MPC), multivariable control design, or machine learning for process control.
Experience with industrial automation platforms such as Honeywell Experion, Emerson DeltaV, Yokogawa CENTUM, or Rockwell ControlLogix.
Enough Data Engineering and Analytics competency to make data-driven applications
Optimization under uncertainty and advanced process simulation (Aspen Plus, HYSYS, gPROMS).

Responsibilities

Design, implement, and optimize control strategies for continuous and batch chemical processes.
Develop dynamic process models (first principles and empirical) to simulate plant behavior and evaluate control performance.
Tune, maintain, and troubleshoot regulatory and advanced control loops (PID, cascade, feedforward, inferential).
Collaborate with operations, R&D, and IT teams to deploy model predictive control (MPC), real-time optimization (RTO), and digital twin solutions.
Support process hazard analysis (PHA), management of change (MOC), and safety interlock design (SIS logic).
Analyze plant performance using statistical tools and control system data to identify process bottlenecks and improvement opportunities.
Provide mentorship to junior engineers in control concepts and automation systems.