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Linear Programming Jobs in Austin, TX (NOW HIRING)

Xpedient Technologies, LLC

AI/ML Engineer

Austin, TX · On-site

We are seeking an experienced AI/ML Engineer with 5+ years of hands-on experience building ... Strong understanding of statistics, linear algebra, and probability * Excellent problem-solving and ...

New

ICON

Senior Robotics Software Engineer I

Austin, TX

$121K - $160K/yr

Experience programming industrial robots in high-level languages. * Experience in formal control theory and linear algebra. * A general understanding of how to manage redundant kinematic chains or ...

Magic Leap

Sr Mechanical Engineer, Equipment Design

Austin, TX · On-site

$89K - $122K/yr

Design and integrate precision mechanical systems, including robotics, linear motors, encoders, air ... Bachelor's degree in Mechanical Engineering. * Proven expertise in designing systems with micron ...

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All JobsLinear Programming JobsLinear Programming Jobs in Austin, TX

Linear Programming information

See Austin, TX salary details

$44.1K

$70.2K

$98.1K

How much do linear programming jobs pay per year?

As of Jul 17, 2026, the average yearly pay for linear programming in Austin, TX is $70,234.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,600.00 and $87,700.00 per year, depending on experience, location, and employer.

What careers use linear programming?

Linear programming is used in careers such as operations research analysts, supply chain managers, financial analysts, and data scientists to optimize processes, resource allocation, and decision-making. These roles often require skills in mathematical modeling, programming, and analytical tools like Excel, MATLAB, or specialized optimization software.

Is linear programming still useful?

Linear programming is a fundamental technique used in operations research and optimization roles to solve problems involving resource allocation and decision-making. It remains widely applicable in industries such as manufacturing, logistics, finance, and supply chain management, often utilizing software tools like Excel Solver or specialized optimization software. Proficiency in mathematical modeling and analytical skills are important for roles involving linear programming.

What is a Linear Programming job?

A Linear Programming job involves using mathematical optimization techniques to maximize or minimize a particular objective, such as cost reduction or resource allocation, under a set of given constraints. Professionals in this field work with mathematical models, algorithms, and software tools like Python, MATLAB, or specialized solvers. These jobs are common in industries like logistics, finance, operations research, and data science, where efficient decision-making is critical.

What are the key skills and qualifications needed to thrive in the Linear Programming position, and why are they important?

To succeed in a Linear Programming role, you need strong mathematical and analytical skills, typically supported by a degree in operations research, mathematics, or a related quantitative field. Familiarity with optimization software such as CPLEX, Gurobi, or MATLAB, along with programming knowledge in Python or R, is often required. Excellent problem-solving abilities, attention to detail, and clear communication are valuable soft skills in this position. These skills and qualities are crucial for effectively modeling, analyzing, and solving complex optimization problems that drive organizational decision-making.

What job makes $1,000,000 a year?

High-level executive roles such as CEOs, CFOs, and other C-suite positions in large corporations can earn $1,000,000 or more annually, often including bonuses and stock options. Additionally, successful entrepreneurs, top investment bankers, and certain specialized professionals in finance, technology, or consulting may reach this income level with significant experience and performance. These roles typically require advanced skills, extensive experience, and often a combination of leadership and strategic responsibilities.

What jobs pay $500,000 a year in the US?

In the field of linear programming and related quantitative roles, high-paying jobs such as senior data scientists, quantitative analysts, and operations research directors can reach or exceed $500,000 annually, especially with bonuses and stock options. These roles typically require advanced degrees, strong analytical skills, and experience with optimization tools and programming languages like Python or R.

What are the typical responsibilities of someone working in a Linear Programming role?

Professionals specializing in Linear Programming are responsible for developing mathematical models to optimize processes such as resource allocation, scheduling, or logistics. Their daily tasks often include collecting and analyzing data, formulating objective functions and constraints, coding and testing optimization algorithms, and interpreting solutions for practical implementation. Collaboration with cross-functional teams such as data analysts, engineers, and business stakeholders is common to ensure models accurately address real-world challenges. By transforming large and complex datasets into actionable insights, these professionals play a key role in improving efficiency and supporting data-driven decisions across industries.

What are popular job titles related to Linear Programming jobs in Austin, TX? For Linear Programming jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Linear Programming jobs in Austin, TX look for? The top searched job categories for Linear Programming jobs in Austin, TX are:
What cities near Austin, TX are hiring for Linear Programming jobs? Cities near Austin, TX with the most Linear Programming job openings:
Linear Programming jobs near you

R&D Data Scientist: Mathematical Modeling and Optimization

Liftlab Analytics, Inc.

Austin, TX • On-site, Remote

Full-time

Re-posted 27 days ago

Job description

(Fully-remote US position)
About LiftLab
Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance.
Job responsibilities
  • Develop new algorithm-based features of LiftLab's marketing measurement and optimization platform
  • Performs diagnostics and root-cause analysis and provide fixes
  • Works with Data Science and Engineering to implement these features into LiftLabs product and workflow
Course work/experience:
  • Data manipulation
    • SQL
    • Operating on big datasets in Python
    • Data visualization
  • Mathematical optimization
    • Linear optimization concepts
    • Nonlinear continuous optimization
    • Linear algebra
  • Mathematical modeling
    • Using parametrized systems of equations to represent real-world systems
  • Statistics
    • Multivariate regression
    • Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters
    • Bayesian concepts
    • Hypotheses testing
Education requirements
Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience
Skills/Aptitude
  • Engineering and detective mindset
    • Both to diagnose data and existing algorithms and to develop new analytics functionality
  • Pragmatic approach to real-world problems
  • Focus on problem solving over applying specific models
  • Willingness to make approximations and assumptions rather than find "the" optimal solution
  • Ability to combine multiple techniques and models to solve end-to end-problems
  • Communication and collaboration skill
  • Ability to convert non-technical requests into project specifications

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