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Linear Programming Jobs in Austin, TX (NOW HIRING)

Neurophos Inc

Senior ML Engineer, Optimization

Austin, TX · On-site

$160K - $215K/yr

Instead of traditional electronic circuits, we use silicon photonics and an active, programmable ... Strong knowledge of numerical linear algebra, including matrix factorizations, conditioning ...

Hired Recruiters

Software Engineer

Austin, TX · On-site +1

Strong programming skills in $LANGUAGES, ideally Python is in the mix * A feel for moderately complex asynchronous systems and building linear user experiences on top of them * Familiarity with AWS:

Apptronik

Senior Perception Hardware Engineer

Austin, TX · On-site

$109K - $146K/yr

... linear optimization (least-squares, bundle adjustment). * Software Proficiency: Strong programming skills in Python and C++ . Extensive experience with computer vision libraries (OpenCV, PCL) and ...

Xoriant Corporation

GPU Software Engineer

Austin, TX · On-site

... C++ programming * Problem-solving and communication skills * 5+ years of object-oriented and ... Knowledge of ray tracing, rasterization, and linear algebra * Experience with low level performance ...

Xoriant Corporation

GPU Software Engineer

Austin, TX · On-site

... C++ programming * Problem-solving and communication skills * 5+ years of object-oriented and ... Knowledge of ray tracing, rasterization, and linear algebra * Experience with low level performance ...

Raytheon

Principal Electronics Engineer

Austin, TX

$137K - $168K/yr

Design, analysis, test, and/or simulation experience with linear converters and any of the ... Advanced degree in Electrical Engineering * Understanding of switching converter control techniques ...

Apptronik

Senior Perception Hardware Engineer

Austin, TX · On-site

$109K - $146K/yr

... linear optimization (least-squares, bundle adjustment). * Software Proficiency: Strong programming skills in Python and C++ . Extensive experience with computer vision libraries (OpenCV, PCL) and ...

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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

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How much do linear programming jobs pay per year?

As of Sep 3, 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 is a linear programming?

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 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 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 careers use linear programming?

Linear programming is used in careers such as operations research analysts, supply chain managers, financial analysts, and industrial engineers. These roles involve optimizing processes, resource allocation, and decision-making using mathematical models and tools like Excel Solver or specialized software. Strong analytical skills and knowledge of optimization techniques are essential in these fields.

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
Infographic showing various Linear Programming job openings in Austin, TX as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $70,234 per year, or $33.8 per hour.

Senior ML Engineer, Optimization

Neurophos Inc

Austin, TX • On-site

$160K - $215K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

About Neurophos
The demand for new data centers and AI compute is rapidly outpacing the planet's energy capacity. Digital solutions are hitting a power wall as we approach the physical limits of traditional silicon. Conquering this bottleneck means rethinking the fundamental architecture of inference compute. The industry's current path can't meet the need, so we're taking a different approach.
Instead of traditional electronic circuits, we use silicon photonics and an active, programmable metasurface to perform matrix multiplications at the speed of light. Our optical cells are 10,000x smaller than traditional photonic components, enabling unprecedented density. By using photonics instead of electricity, our chips become more efficient as they scale. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving performance for large-scale AI inference.
We've assembled a world-class team of industry veterans and recently raised a $110M Series A led by Gates Frontier. Participants include M12 (Microsoft's Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others.
Join us and shape the future of computing!
Location: Austin, TX or Sunnyvale, CA. Full-time onsite position.
Reports To: Mathematics and Quantization Lead
FLSA Status: Exempt
Position Overview
We are seeking an experienced machine learning engineer to develop advanced post-training quantization methods for large language models (LLMs), diffusion models, and other ML applications for our revolutionary optical inference engines. This role is critical to demonstrating the full potential of our metamaterial-based optical processing units (OPUs) by adapting state-of-the-art AI models to leverage our ultra-high-throughput, low-precision compute architecture.
The ideal candidate will bridge the gap between cutting-edge ML research and novel hardware capabilities, ensuring customers can seamlessly deploy their AI workloads on Neurophos hardware.
Key Responsibilities
  • Develop and execute hardware-aware post-training methods for full model quantization.
  • Investigate preconditioning and formulate quantization as non-convex, discrete, constrained, or second-order optimization and develop practical solutions.
  • Contribute to refining Neurophos's quantization strategy.
  • Design controlled numerical experiments to understand potential improvements and secondary effects due to analog processing hardware.
  • Build research-quality implementations and reproducible experiment harnesses for testing candidate methods.
  • Adapt models from open-source repositories and customer private models.
  • Work with models in various formats, including PyTorch, Triton, JAX, and emerging frameworks.
  • Design and execute re-quantization, retraining, and other model adaptation techniques to minimize accuracy loss during precision reduction.
  • Optimize GEMM operations for high-throughput execution.
  • Collaborate with hardware, software, and architecture teams to co-optimize model architectures for optical compute characteristics.
  • Publish research papers on novel optimization techniques and methodologies, with appropriate IP protection.

Qualifications
  • PhD, or equivalent research experience, in machine learning, applied mathematics, optimization, numerical analysis, computer science, or a closely related field
  • 5+ years of experience in machine learning engineering, with at least 3 years focused on model optimization and deployment.
  • Research or advanced engineering experience in neural network quantization, model compression, numerical optimization, or efficient inference.
  • Strong knowledge of numerical linear algebra, including matrix factorizations, conditioning, covariance estimation, and iterative methods.
  • Experience with one or more of non-convex optimization, discrete optimization, manifold optimization, second-order methods, or constrained optimization.
  • Strong proficiency in PyTorch and familiarity with other ML frameworks, including JAX, Triton, and TensorFlow.
  • Hands-on experience with transformer architectures, LLMs, and diffusion models.
  • Experience designing controlled numerical experiments and distinguishing algorithmic improvements from calibration or benchmark artifacts.
  • Strong written communication and research collaboration skills.

Preferred Skills
  • Experience with low-precision inference optimization (INT8, FP8, or lower).
  • Background in analog or optical computing architectures.
  • Knowledge of in-memory computing paradigms and matrix-vector multiplication acceleration.
  • Knowledge of randomized numerical linear algebra, sketching, or structured transforms.
  • Publications in quantization, optimization, numerical linear algebra, model compression, or efficient ML.
  • Experience with vector quantization, lattice methods, learned codebooks, or rate-distortion ideas.
  • Experience with large-scale batch inference optimization.
  • Familiarity with prefill versus decode optimization strategies in LLM inference.
  • Experience conducting experiments on models large enough to expose scaling and generalization problems.

What We Offer
This is an opportunity to play a pivotal role in an innovative startup redefining the future of AI hardware. Work on game-changing technology at the intersection of photonics and AI as part of a collaborative, brilliant team. You'll contribute to a platform that redefines computational performance and accelerates the future of artificial intelligence. Come help us bring this transformative technology to the world.
Benefits
Join a team that invests in your future and your well-being. At Neurophos, we offer:
  • 100% coverage of base health plan premiums for you and your dependents, plus HSA contributions.
  • Unlimited PTO. No rigid vacation banks, just a focus on delivery.
  • 401(k) matching and stock option opportunities to ensure our success is your success.
  • Full suite of voluntary benefits, including Dental, Vision, Life, Hospital, Critical Illness, and Accident insurance.
  • Personalized Benefits. Choose the plans that fit your life and take the cash back for those that don't.

Apply