ZipRecruiter

Log In

1

Constraint Programming Jobs (NOW HIRING)

Intel

Operations Research Engineer

Folsom, CA · On-site

$149K - $211K/yr

Programming proficiency in C# and experience working with commercial optimization and constraint programming job shop scheduling packages such as ILOG CPLEX, Gurobi, Autosched, and similar platforms.

Intel

Operations Research Engineer

Phoenix, AZ · On-site

$149K - $211K/yr

Programming proficiency in C# and experience working with commercial optimization and constraint programming job shop scheduling packages such as ILOG CPLEX, Gurobi, Autosched, and similar platforms.

Intel

Operations Research Engineer

Hillsboro, OR · On-site

$149K - $211K/yr

Programming proficiency in C# and experience working with commercial optimization and constraint programming job shop scheduling packages such as ILOG CPLEX, Gurobi, Autosched, and similar platforms.

Intel Corporation

Operations Research Engineer

Phoenix, AZ · On-site

$149K - $211K/yr

Programming proficiency in C# and experience working with commercial optimization and constraint programming job shop scheduling packages such as ILOG CPLEX, Gurobi, Autosched, and similar platforms.

next page

Showing results 1-20

All JobsConstraint Programming Jobs

Constraint Programming information

See salary details

$44.5K

$70.9K

$99K

How much do constraint programming jobs pay per year?

As of Jul 30, 2026, the average yearly pay for constraint programming in the United States is $70,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,000.00 and $88,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Constraint Programming Specialist, and why are they important?

To thrive as a Constraint Programming Specialist, you need a strong background in computer science, discrete mathematics, and optimization, typically with a relevant degree. Proficiency in programming languages like Python or C++, and experience with constraint programming libraries or solvers such as Google OR-Tools or IBM ILOG CPLEX, are essential. Analytical thinking, problem-solving, and effective communication are key soft skills that help in translating real-world problems into constraint models and collaborating with stakeholders. These skills are crucial for developing efficient solutions to complex scheduling, planning, and resource allocation problems in various industries.

What is constraint programming?

Constraint programming is a computational paradigm used to solve complex combinatorial problems by specifying constraints that need to be satisfied. Instead of outlining a step-by-step procedure, you define the properties a solution must have, and the constraint solver finds solutions that meet these requirements. It's commonly applied in scheduling, planning, resource allocation, and other optimization tasks. This method is widely used in fields like operations research, artificial intelligence, and computer science to efficiently tackle problems that are otherwise hard to solve.

What are some common challenges faced by professionals working in constraint programming roles?

Professionals in constraint programming often encounter challenges such as efficiently modeling complex real-world problems and selecting the most suitable algorithms for solving them. Balancing solution accuracy with computational efficiency is a frequent concern, especially when working with large-scale datasets or time-sensitive applications. Collaboration with domain experts is also key, as understanding the specific requirements and constraints of each project is crucial for developing effective solutions. Additionally, staying updated with the latest advances in solvers and optimization techniques is important for maintaining a competitive edge in this field.

What is the difference between Constraint Programming vs Data Analyst?

AspectConstraint ProgrammingData Analyst
Required CredentialsTypically a degree in Computer Science, Operations Research, or related fieldsUsually a degree in Statistics, Mathematics, or Business
Work EnvironmentSoftware development, optimization projects, algorithm designData analysis, reporting, data visualization
Industry UsageOperations research, logistics, scheduling, AIFinance, marketing, healthcare, retail

Constraint Programming focuses on solving complex combinatorial problems through algorithms and constraints, often in software or operations research. Data Analysts interpret and visualize data to support business decisions. While both roles involve working with data and algorithms, Constraint Programming is more technical and algorithm-driven, whereas Data Analysts focus on data interpretation and reporting.

More about Constraint Programming jobs
What cities are hiring for Constraint Programming jobs? Cities with the most Constraint Programming job openings:
What job categories do people searching Constraint Programming jobs look for? The top searched job categories for Constraint Programming jobs are:
Constraint Programming jobs near you
Infographic showing various Constraint Programming job openings in the United States as of July 2026, with employment types broken down into 15% Internship, 80% Full Time, 1% Part Time, 1% Contract, and 3% Summer. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $70,857 per year, or $34.1 per hour.

Operations Research / Systems Analyst (ORSA) - Optimization & Mathematical Programming

SMX

Hanover, MD

$98K - $115K/yr

Other

Posted 14 days ago

Job description

The Operations Research (OR) Analyst - Optimization & Mathematical Programming Focus provides advanced optimization, resource allocation, and prescriptive analytics across a Federal Agency's personnel vetting, industrial security, and counterintelligence operations. This position formulates and solves complex mathematical programming problems that enable the Federal Agency to optimize resource deployment, prioritize competing requirements, and transition from reactive decision-making toward mathematically grounded, optimal resource allocation strategies.

Essential Duties and Responsibilities

Mathematical Optimization & Resource Allocation

  • Formulate real-world resource allocation problems as mathematical optimization models (linear programming, integer programming, mixed-integer programming)
  • Develop and implement optimization algorithms for complex assignment problems including adjudicator workload distribution, facility inspection scheduling, and investigator allocation
  • Apply constraint programming and heuristic methods to solve large-scale, computationally challenging optimization problems
  • Build decision support tools that enable operational leaders to explore tradeoffs and make resource deployment decisions with mathematical rigor

Strategic Analysis & Decision Support

  • Conduct cost-benefit analyses and apply mathematical programming techniques to optimize the distribution of personnel, budgetary, and operational resources across competing requirements
  • Apply risk-based optimization to prioritize facility assessments, case assignments, and inspection schedules based on threat levels and resource constraints
  • Perform trade-space analysis and sensitivity studies to understand how optimal solutions change under different assumptions, constraints, or objectives
  • Develop multi-objective optimization approaches that balance competing goals (speed, quality, cost, risk mitigation)

Model Development & Implementation

  • Utilize optimization solvers (Gurobi, CPLEX, or open-source alternatives like Pyomo, PuLP, OR-Tools) to implement and solve mathematical models
  • Validate optimization model outputs against historical operational data and subject matter expert judgment
  • Develop prescriptive analytics that recommend specific actions based on optimization results
  • Create scenario planning tools that allow decision-makers to explore "what-if" questions regarding resource allocation strategies

Collaboration & Communication

  • Work closely with modeling/simulation specialists to incorporate predictive analytics into optimization formulations
  • Partner with data engineering specialists to obtain empirically-grounded parameters, constraints, and objective function coefficients
  • Translate mathematical optimization results into clear, actionable recommendations for non-technical decision-makers
  • Present optimization approaches, tradeoff analyses, and recommendations to senior leadership
  • Participate in cross-functional team activities to maintain technical standards and share knowledge

Required Skills & Experience 

  • 8+ years of progressive, hands-on operations research experience, including demonstrated application of mathematical optimization, resource allocation modeling, and prescriptive analytics to real-world operational problems
  • 3-5 years of that experience supporting DoD or Intelligence Community mission areas such as personnel vetting, industrial security (NISP), counterintelligence, or insider threat
  • Expert-level proficiency in mathematical optimization including linear programming, integer programming, and mixed-integer programming
  • Hands-on experience with optimization solvers (Gurobi, CPLEX, FICO Xpress, or open-source alternatives such as Pyomo, PuLP, OR-Tools, COIN-OR)
  • Demonstrated ability to formulate real-world problems as mathematical programs, including objective function design and constraint identification
  • Proven proficiency in an analytical programming language (Python or R), with emphasis on optimization modeling libraries
  • Experience with constraint programming and heuristic solution methods for large-scale or computationally difficult problems
  • Strong foundation in algorithm design, computational complexity, and solution methods
  • Ability to validate optimization models using operational data and communicate results to non-technical stakeholders
  • Experience working in secure (classified) government environments
  • Secret clearance required (active or ability to obtain)

Desired Skills & Experience 

  • Advanced degree in Operations Research, Applied Mathematics, Industrial Engineering, Management Science, or a related quantitative discipline
  • Familiarity with NISP, clearance adjudication processes, and/or insider threat/counterintelligence analytic frameworks
  • Experience with nonlinear optimization and stochastic optimization techniques
  • Knowledge of multi-objective optimization and Pareto analysis
  • Network optimization and graph algorithms (shortest path, max flow, matching problems)
  • Experience with scheduling and routing problems (job shop scheduling, vehicle routing)
  • Familiarity with game theory and decision analysis under uncertainty
  • Knowledge of operations research software (AMPL, GAMS)
  • Data visualization tools (Tableau, Power BI) for communicating optimization results
  • SQL and database querying skills to support model parameterization
  • Knowledge of queueing theory and simulation to better integrate with modeling specialists
  • Experience with statistical modeling and risk analysis to inform optimization formulations

Application Deadline:  July 31, 2026

Apply