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Model Predictive Control Jobs in Pennsylvania (NOW HIRING)

Merck & Co.

... predictive scientists, translate business needs into scalable digital capabilities, and ensure ... Champion the development and deployment of in silico modeling.Change Management: Partner with ...

Govini

Data Scientist

Pittsburgh, PA · On-site

Apply advanced statistical and predictive modeling techniques to build, maintain, and improve ... Familiarity with Git source control management * Experience working in a product organization

Govini

Data Scientist

Pittsburgh, PA · On-site

Apply advanced statistical and predictive modeling techniques to build, maintain, and improve ... Familiarity with Git source control management * Experience working in a product organization

Govini

Data Scientist

Pittsburgh, PA

Apply advanced statistical and predictive modeling techniques to build, maintain, and improve ... Familiarity with Git source control management * Experience working in a product organization

System One Holdings, LLC

Enterprise Engineer

Pittsburgh, PA · On-site

$103K - $129K/yr

Collaborate closely with security teams on NAC, identity?based access control, and policy ... Experience working within Agile or iterative delivery models for enterprise network initiatives

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Model Predictive Control information

What is Model Predictive Control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What are the typical challenges faced by engineers working with Model Predictive Control (MPC) systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What are the key skills and qualifications needed to thrive as a Model Predictive Control (MPC) Engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.
What are popular job titles related to Model Predictive Control jobs in Pennsylvania? For Model Predictive Control jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Model Predictive Control jobs in Pennsylvania look for? The top searched job categories for Model Predictive Control jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Model Predictive Control jobs? Cities in Pennsylvania with the most Model Predictive Control job openings:
Model Predictive Control jobs near you
Process & Automation Equipment Engineer

Process & Automation Equipment Engineer

Krystal Biotech

Pittsburgh, PA • On-site

Full-time

Posted 3 days ago

Job description

Process & Automation Equipment Engineer
About Krystal Bio: At Krystal Biotech, we bring together the brightest and most eager minds to relentlessly pursue the discovery, development, manufacturing, and commercialization of genetic medicines to treat diseases with high unmet medical needs.
Founded in 2016, Krystal is distinguished in three powerful ways: science and technology using our patented gene therapy platform, innovative manufacturing supported by our commercial scale facilities, and a unique commercialization model that focuses on the patient's end-to-end experience.
Krystal received U.S. FDA approval for the first and only redosable gene therapy treatment, VYJUVEK®, for the treatment of Dystrophic Epidermolysis Bullosa (DEB). Krystal continues to leverage our proprietary platform to rapidly advance a robust pipeline of investigational genetic medicines in respiratory, oncology, dermatology, and ophthalmology.
Krystal is headquartered in Pittsburgh, PA, which is home to our two state-of-the-art CGMP manufacturing facilities with teams around the world and satellite offices in Switzerland, Germany, and Japan. We are a company built and run by people who care, are fearless in the face of a challenge, love the work they do, and practice the highest level of scientific integrity. As we grow, we are seeking team members that embody these values.
Job Description Summary:
Krystal Biotech is seeking a motivated and data-driven manufacturing engineer to lead troubleshooting efforts and optimization of GMP manufacturing processes. The Engineer will integrate process engineering, automation, and data analytics, while supporting the development of data-driven monitoring and predictive maintenance programs, along with intelligent manufacturing capabilities. This role is ideal for an engineer with a passion for automation and process optimization, with interest in becoming a subject matter expert on the control systems that drive our gene therapy manufacturing platform. This role serves as a technical bridge between Manufacturing, Automation, and Facilities, ensuring seamless integration of process equipment, control systems maintenance, and facility infrastructure.
Primary Responsibilities:
  • Act as the primary interface between Manufacturing, Automation, and Facilities teams to diagnose and resolve process and equipment issues spanning control systems, utilities, and unit operations.
  • Support day-to-day upstream manufacturing operations, ensuring equipment and processes are operating within validated parameters.
  • Develop deep familiarity with control systems (PLCs, HMIs, and SCADA) associated with manufacturing processes with a long-term goal to predictive maintenance of process equipment
  • Partner with the Automation and Facilities teams to troubleshoot issues across process equipment, control systems, and supporting utilities (HVAC, gases, etc.)
  • Identify opportunities to optimize existing automation configurations, batch record workflows, and data collection tools to improve process efficiency and data integrity.
  • Assist in the authoring and review of SOPs, batch records, work orders, change controls, and deviations related to upstream process and automation activities.
  • Support equipment qualification, process validation, and technology transfer activities as they relate to upstream systems and associated control infrastructure.
  • Collaborate with Process Development and Manufacturing Sciences to ensure alignment between process design intent and real-world automation behavior.
  • Contribute to continuous improvement initiatives and help foster a culture of proactive problem-solving across CMC functions.

Minimum Qualifications & Desired Competencies:
  • Bachelor's degree in Engineering, or a relevant technical field
  • Prior experience in a regulated manufacturing or process engineering environment is preferred (biotech, pharmaceutical, or adjacent industry)
  • Exposure to industrial automation systems such as PLCs, HMIs, and/or SCADA platforms; hands-on experience is a plus
  • Familiarity with GMP principles and documentation standards
  • Background in upstream bioprocessing, cell culture, or bioreactor operations is a plus
  • Solid process engineering background in biologics / CGT GMP manufacturing
  • Hands-on experience with process equipment troubleshooting (e.g., Bioreactors/ skids/ fillers/ mixers and single-use systems)
  • Working knowledge of process controls and automation systems (hands-on experience with at least one platform preferred)
    • PLC (Allen-Bradley, Siemens) or equivalent
    • SCADA (FactoryTalk SE / Ignition / DeltaV) or equivalent
    • HMI (FactoryTalk ME / TIA Portal) or equivalent
  • Demonstrated experience with instrument or equipment control application software. SME level preferred.
  • Basic understanding of facilities/utilities systems (HVAC, cleanrooms)
  • Experience with process data and historians (e.g., OSI PI) and Familiarity with data analysis tools (e.g., Excel, Python, or similar)
  • Interest in applying data analytics for troubleshooting and process improvement
  • Exposure to predictive maintenance or anomaly detection is a plus
  • Awareness of advanced process control or model-based approaches (nice-to-have)
  • Strong troubleshooting mindset for real-time manufacturing support, Experience with root cause analysis (RCA, FMEA), Familiarity with deviation/CAPA processes in GMP environments and Ability to operate effectively at the interface of process, automation, and facilities teams
  • Strong cross-functional collaboration (MSAT, QA, Facilities, IT) and Ability to translate process issues into data-driven insights
  • Interest in supporting digital / smart manufacturing initiatives
  • Strong analytical and troubleshooting skills with a methodical, detail-oriented approach
  • Ability to work collaboratively across functions and communicate effectively with both technical and non-technical stakeholders
  • Self-starter who can manage competing priorities in a fast-paced, evolving environment
  • Excellent written and oral communication skills

Krystal Biotech, Inc. is an Equal Employment Opportunity and Affirmative Action Employers. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Krystal Biotech, Inc. does not accept unsolicited headhunter and agency resumes. Krystal Biotech, Inc. will not pay fees to any third-party agency or company that does not have a signed agreement with Krystal Biotech, Inc.

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