1

Model Predictive Control Jobs in Jackson, MS (NOW HIRING)

AI Security Lead

Ridgeland, MS ยท On-site

$175K/yr

... generative / predictive models. Perform code reviews and penetration testing to detect ... Develop Role-Based Access Control (RBAC) and security filters to prevent models from generating ...

AI Security Lead

Ridgeland, MS ยท On-site

$175K/yr

... generative / predictive models. Perform code reviews and penetration testing to detect ... Develop Role-Based Access Control (RBAC) and security filters to prevent models from generating ...

Talent Community Hinds Community College

Brandon, MS ยท On-site

$18.25 - $22.25/hr

... Predictive Maintenance (PdM) tools, and your maintenance knowledge to supervise and resolve ... Install, maintain, and solve relay logic, ladder diagrams, control components, photo-eyes, motor ...

Model Predictive Control information

See Jackson, MS salary details

$47.9K

$84.2K

$114.2K

How much do model predictive control jobs pay per year?

As of Sep 14, 2026, the average yearly pay for model predictive control in Jackson, MS is $84,157.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,800.00 and $94,100.00 per year, depending on experience, location, and employer.

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 are the typical challenges faced by engineers working with model predictive control 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 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 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 does a model predictive control do?

A Model Predictive Control (MPC) engineer designs control systems that use a mathematical model to predict future system behavior and optimize control actions accordingly. MPC is commonly used in industries like process control and robotics, requiring skills in control theory, programming, and system modeling. The role involves developing algorithms, tuning controllers, and ensuring system stability and efficiency.

What job categories do people searching Model Predictive Control jobs in Jackson, MS look for?

The top searched job categories for Model Predictive Control jobs in Jackson, MS are:

Infographic showing various Model Predictive Control job openings in Jackson, MS as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, 3% Contract, and 1% Nights. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $84,157 per year, or $40.5 per hour.

AI Security Lead

Ridgeland, MS โ€ข On-site

Apex Systems
IT Servicesย โ€ขย 1 - 5K employees

$175K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 12 days ago


Job description

Job#: 3048991
Job Description:
Location: Remote
Duration: 6 month contract to hire
Rate: conversion up to $175k
We are seeking an accomplished and strategic AI Security Architect to create the foundation of a secure, compliant, and ethical AI platform. In this role, you'll design and lead enterprise security frameworks for product engineering and client deployments. You'll integrate cybersecurity, risk management, and AI/GenAI lifecycle governance to protect sensitive data and models from emerging threats while meeting regulatory and client obligations. You will protect our AI platform and GenAI agents from vulnerabilities (e.g., prompt injection, data poisoning, leakage) and operate at the intersection of cybersecurity, data, and DevOps to implement AI-specific defenses across the development lifecycle. Your work will be pivotal in mitigating AI-specific risks and enabling innovation in a secure and controlled environment.
Responsibilities
Secure by Design: Designs secure AI infrastructure, ensuring confidentiality, integrity, and availability of AI pipelines (training, monitoring, deployment). Secures autonomous AI agents, ensuring they do not deviate from their safety baseline
  • Collaborate and Influence: Build strong team collaboration to ensure security is embedded from design through implementation in products and services.
  • Be the Expert: Act as a trusted advisor and subject matter expert across security domains, guiding stakeholders on best practices.
  • Governance: Create and implement client delivery security and governance frameworks that promote ethical, secure, and compliant AI use.
  • Set Standards: Develop and enforce AI security standards aligned with regulatory and industry benchmarks (ISO 42001, NIST AI RMF, SANS, CSA, OWASP).
  • Secure Azure Cloud Deployments: Oversee solution deployment in our Azure cloud environment with robust data protection and encryption.
  • Assess and Vulnerability Test: Conduct AI security risk assessments, threat modeling, and red team exercises for generative / predictive models. Perform code reviews and penetration testing to detect misconfiguration or data exposure risks.
  • Threat Modeling: Design security frameworks to proactively identify and mitigate risks specific to AI, such as adversarial attacks and jailbreaking.
  • Respond and Remediate: Support AI security incident response and ensure effective remediation processes.

Pipeline Security: Secure the entire AI lifecycle, including training data integrity, model endpoints, and memory systems.
Implementation of Guardrails: Develop Role-Based Access Control (RBAC) and security filters to prevent models from generating unsafe or unethical outputs.
Required Qualifications
  • Proven experience leading AI security teams in building enterprise-grade platforms on Azure.
  • Deep expertise in cloud architecture, distributed systems, and scalable frameworks.
  • Advanced proficiency in GenAI, agent-based systems, and LLMs. Understanding of agent frameworks (e.g., LangChain, Semantic Kernel) and orchestration tools.
  • Strong background in data engineering, including ETL, data lakes, and real-time processing.
  • Demonstrated ability to design secure, compliant, and reliable cloud solutions.
  • Proven success implementing governance frameworks, risk strategies, and compliance programs for emerging technologies.
  • Strong background in Python, AI/ML lifecycle management, neural networks, and cybersecurity within AI
  • Experience working with auditors, regulators, and compliance teams.
  • Proficiency in cloud-native AI/ML platforms (AWS SageMaker, Bedrock, Azure AI, Google Cloud Platform Vertex).
  • Familiarity with security frameworks (NIST, ISO 27001, ISO 42001, CIS Controls). Government / Public Sector experience is preferred.
  • Strong communication skills and ability to engage with stakeholders at all levels.
  • Ability to work independently in a fast-paced environment while fostering collaboration and creative problem-solving.
  • Leadership skills to mentor and guide team members effectively.

Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico.
Everforth Apex uses a virtual recruiter as part of the application process. Click for more details. By applying for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Everforth Apex and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at
Everforth Apex Benefits Overview: Everforth Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Everforth Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Everforth Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Everforth Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our 'Welcome Packet' as well, which an Everforth Apex team member can provide.
Everforth Apex Systems is an equal opportunity employer. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law. Everforth Apex will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable law.
If you require an accommodation under the Americans with Disabilities Act to participate in an interview with a virtual recruiter or to use our website for a search or application, please contact our Benefits Department at or . Please note that this contact information is strictly to be used for medical ADA accommodations and that no other inquiries will be answered.
UnitedHealthcare creates and publishes the Transparency in Coverage Machine-Readable Files on behalf of Everforth Apex Systems.