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Convex Optimization Jobs in California (NOW HIRING)

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

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 ...

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

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

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

Knowledgeable in network topology, numerical optimization techniques, graph theoretic approaches, or convex optimization * Developed, debugged, and deployed software that has been used in real world ...

Knowledgeable in network topology, numerical optimization techniques, graph theory approaches, or convex optimization. * Developed, debugged, and deployed scalable software that has been used in real ...

Showing results 21-40

Convex Optimization information

See California salary details

$15.8K

$55.1K

$100.7K

How much do convex optimization jobs pay per year?

As of Sep 4, 2026, the average yearly pay for convex optimization in California is $55,064.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $71,600.00 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.

What are the most commonly searched types of Convex Optimization jobs in California?

The most popular types of Convex Optimization jobs in California are:

What cities in California are hiring for Convex Optimization jobs?

Cities in California with the most Convex Optimization job openings:

Infographic showing various Convex Optimization job openings in California as of August 2026, with employment types broken down into 88% Full Time, 10% Part Time, and 2% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $55,064 per year, or $26.5 per hour.

Senior Motion Planning Software Engineer

Namely

South San Francisco, CA • On-site

$120 - $180/hr

Other

Re-posted 18 hours ago


Key responsibilities

  • Build real-time trajectory generation and decision-making for autonomous flight.

  • Tackle joint optimization across safety, energy, time, and reliability while considering vehicle constraints.

  • Design safety-critical software for obstacle avoidance and human interface during delivery and pickup operations.


Job description

About Zipline

Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.


Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations.


Our system strengths supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.


We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.


About You and The Role

Zipline operates the world's largest autonomous logistics system (ground or air) - and in the coming year, we will be hyper-scaling from thousands to tens of thousands of carefully coordinated drone deliveries in several dense, dynamic U.S. metros. Our Autonomy Motion Planning team is looking for a Senior Software Engineer who is passionate about developing autonomous systems for the real world. This role will explore cutting-edge approaches to decision making and trajectory planning that will enable more accurate and timely deliveries, putting you in the position to make critical product decisions that will shape our future architectures.


What You'll Do

  • Build real-time trajectory generation and decision-making for autonomous flight (search-based, sampling, MPC, convex/non-convex optimization).

  • Tackle joint optimization across safety, energy, time, and reliability-balancing mission goals with vehicle constraints.

  • Plan in uncertain environments with complex dynamics: robustness to wind/turbulence, degraded sensors, and partial observability.

  • Design safety-critical software for avoiding obstacles and interfacing with humans while delivering and picking up packages

  • Extend the autonomy stack for new aircraft and payloads; define clean interfaces with perception and controls.

  • Prove it before flight: large-scale sim, SIL/HIL, log replay, and fault-injection.

  • Mine real fleet data to validate safety metrics, improve models, and burn down long-tail failure modes.


What You'll Bring

  • Master's degree in Computer Science or related field and 3+ years of experience building software for safety-critical systems (aerospace/AV/robotics).

  • Strong in Rust/C++/C for real-time, fault-tolerant code on embedded/Linux.

  • Depth in planning & search (e.g. A*/ anytime / RRT*/sampling), trajectory optimization/MPC - shipped on real robots/vehicles.

  • Hands-on with simulation at scale, SIL/HIL, log replay, and metrics-driven validation.

  • Evidence of shipping production-grade autonomy through ambiguous, noisy conditions - owning the last mile to reliability.

  • Systems thinker who collaborates tightly with perception, controls, and flight ops; crisp docs and design reviews.


What Else You Need To Know

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.


We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

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