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Convex Optimization Jobs (NOW HIRING)

CONTROLNET

Vehicle Control Research Engineer

San Diego, CA · On-site

$150K - $180K/yr

Knowledge and experience in convex optimization, non‑linear optimization, stochastic optimization, Markov decision process, and graph search algorithm. * Experience in designing and building data ...

Inversion

Staff GNC Engineer (Guidance)

Vista, CA · On-site

$161K - $221K/yr

Experience with modern convex optimization methods for guidance (e.g., successive convexification / sequential convex programming, lossless convexification) * Experience developing and exercising 3 ...

pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Experience in convex optimization, computational geometry or linear algebra. * Experience in GPU/CUDA/TensorRT * Previous internships involving large-scale deep learning models and systems

Pony.ai

Research Intern - Deep Learning

Fremont, CA · On-site

$7.0K - $10K/mo

Experience in convex optimization, computational geometry or linear algebra. * Experience in GPU/CUDA/TensorRT * Previous internships involving large-scale deep learning models and systems

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How much do convex optimization jobs pay per year?

As of Sep 10, 2026, the average yearly pay for convex optimization in the United States is $55,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $72,500.00 per year, depending on experience, location, and employer.

What is convex optimization?

A Convex Optimization job involves designing, analyzing, and implementing optimization algorithms to solve mathematical problems where the objective function and constraints are convex. Professionals in this field work in areas such as machine learning, finance, engineering, and operations research to improve efficiency and decision-making. They typically have expertise in linear and nonlinear programming, duality theory, and numerical algorithms. Jobs in this field require strong mathematical and programming skills, often using tools like Python, MATLAB, or CVX.

What does someone working in convex optimization do?

Professionals in Convex Optimization often spend their days formulating mathematical models, designing and implementing algorithms to solve optimization problems, and analyzing results to improve performance across various applications. They collaborate with data scientists, engineers, and domain experts to gather requirements and translate real-world challenges into solvable mathematical formulations. Additionally, they may be involved in code deployment, ensuring models are efficient and scalable for production use. Regular teamwork, troubleshooting, and staying current with the latest optimization research are also key parts of the job.

What are the key skills and qualifications needed to thrive in convex optimization?

To thrive in a Convex Optimization role, you need a strong background in mathematics, particularly in optimization theory, linear algebra, and calculus, often supported by an advanced degree in mathematics, engineering, or computer science. Proficiency in programming languages such as Python, MATLAB, or Julia, and familiarity with optimization libraries and tools like CVX or Gurobi, are usually expected. Strong analytical thinking, problem-solving ability, and effective communication skills help you interpret complex problems and convey solutions to interdisciplinary teams. These skills are essential for designing robust optimization models that drive efficiency and innovation in fields like data science, finance, engineering, and operations research.

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Convex Optimization jobs near you
Infographic showing various Convex Optimization job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 7% Part Time, and 3% Contract. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

NIST PREP Postdoc Associate in Quantum Networks Entanglement Layer Research

Gaithersburg, MD • On-site

Southeastern Universities Research Association
11 - 50 employees
Learn more about Southeastern Universities Research Associationexternal

$80K - $90K/yr

Full-time

Re-posted 19 days ago

Job description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title: Quantum Networks Entanglement Layer Research
The work will entail: This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Key responsibilities will include but are not limited to:
  • Characterize and develop models and optimizers for quantum network components.
  • Design optimization and learning algorithms and protocols for entanglement routing in quantum networks.
  • Prototype models, algorithms and experiments in simulated environments, and provide rigorous analyses and evaluations using measurement data from the project experimentation team.
  • Maintain a detailed log of all prototypes, simulations and experimental activities.
  • Share research findings through peer-reviewed journals, conferences, and presentations.

Qualifications
  • A PhD in Electrical and Computer Engineering or a related field is required.
  • Candidates should have research experience in one or more of the following areas: control and communication systems, convex/non-convex optimization, distributed and federated learning, dynamical networked systems; and with at least six (6) years of experience in theoretical and practical design and evaluation of machine learning and optimization algorithms for distributed systems and optimal network resource allocation.
  • A solid understanding of quantum network engineering, control and queueing theories, mathematics is essential, with at least three (3) years of experience working on mechanisms for supporting end-to-end quality of services in an emerging networking technologies.
  • Programming skills for control and communication systems and machine learning are required, with proficiency in languages such as MATLAB and Python, and with at least six (6) years of experience in independent design, efficient implementation, and testing of all aspects of optimization or machine learning algorithms in a testbed.
  • Familiarity with quantum network components and simulators is expected.
  • U.S. Citizen is preferred.

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
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