ZipRecruiter

Log In

1

Convex Optimization Jobs (NOW HIRING)

Federato Technologies

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy

Convex

Software Engineer, AI

San Francisco, CA · On-site

The projects involve range from small ergonomic tweaks to make agentic development seamless, large structural changes like branching and automatic performance optimization of Convex projects, and ...

C3 AI

Data Scientist (Federal)

Virginia, IL

Understanding of optimization (constrained, stochastic, convex and non-convex optimization problems) * Experience working with modern IDEs and AI agent tools as part of accelerated development ...

Federato Technologies

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization), either PhD or Advanced MS degree. * Comfortable with Python, Flask/Django, Pandas and Numpy

Convex

Software Engineer, AI

San Francisco, CA

The projects involve range from small ergonomic tweaks to make agentic development seamless, large structural changes like branching and automatic performance optimization of Convex projects, and ...

Quanta Search

Stat Arb Quant Researcher

Manhattan, NY · On-site

Knowledge of/degree in topics including but not limited to: machine learning/statistical learning, convex optimization, numerical linear algebra, finance, market microstructure * The creativity to ...

Vise

Quantitative Engineer

New York, NY · On-site

$190K - $270K/yr

We work closely with convex optimization techniques and numerical optimizations of various problems. Past exposure in solving complex problems in a numerically optimized way is a plus. What you will ...

Vise

Quantitative Engineer

New York, NY · On-site

$190K - $270K/yr

We work closely with convex optimization techniques and numerical optimizations of various problems. Past exposure in solving complex problems in a numerically optimized way is a plus. What you will ...

next page

Showing results 1-20

All JobsConvex Optimization Jobs

Convex Optimization information

See salary details

$16K

$55.8K

$102K

How much do convex optimization jobs pay per year?

As of Jun 15, 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 are the typical day-to-day tasks of someone working in a Convex Optimization role?

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 the Convex Optimization position, and why are they important?

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 is a Convex Optimization job?

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.

More about Convex Optimization jobs
What cities are hiring for Convex Optimization jobs? Cities with the most Convex Optimization job openings:
What are the most commonly searched types of Convex Optimization jobs? The most popular types of Convex Optimization jobs are:
What states have the most Convex Optimization jobs? States with the most job openings for Convex Optimization jobs include:
What job categories do people searching Convex Optimization jobs look for? The top searched job categories for Convex Optimization jobs are:
Convex Optimization jobs near you
Infographic showing various Convex Optimization job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 78% Physical, 15% Hybrid, and 7% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Staff Computational Scientist, Grid Optimization, (Tapestry)

X, the moonshot factory

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Job description

S t a f f C o m p u t a t i o n a l S c i e n t i s t , G r i d O p t i m i z a t i o n , ( T a p e s t r y )
Software Engineering Mountain View, CA (HQ)
About Tapestry
Tapestry is Alphabet's moonshot for the electric grid, working at the frontier where energy's complexity meets AI's potential. We were born at X, the innovation lab responsible for breakthrough technologies like Waymo, Verily and Google Brain.
To keep pace with humanity's growing energy needs, the world needs a grid that is visible and understandable. We provide that clarity by building advanced, AI-enabled analytical and planning tools that allow the entire energy ecosystem to plan smarter, move faster, and operate more efficiently-ensuring electricity remains reliable and affordable for everyone.
This is a global effort. Tapestry is proud to support partners in the U.S., U.K., Chile, New Zealand, Australia and Brazil as they build a cleaner, more resilient energy future.
Joining Tapestry allows you to do the best work of your life as part of a multidisciplinary team of experts in AI, energy systems, software engineering and product design-all collaborating to reshape energy on a global scale. If you want to tackle problems that matter and build tools with real impact, we would love to meet you. Learn more about our team and our mission here .
About the role:
As a Computational Scientist in Grid Optimization, you will be the architect of the decision-making logic that powers Tapestry. This is a high-seniority role designed for an expert who can bridge the gap between deep mathematical theory and high-performance software execution. You won't just be using existing solvers; you will be evolving our internal optimization engines to handle the unprecedented complexity of modern energy resources.
You will lead the design of scalable solvers for critical grid functions like ACOPF, SCED, and SCUC, ensuring they are fast enough and robust enough for real-world deployment. If you are passionate about translating complex non-convex optimization problems into production-ready code that changes how the world uses energy, we want to talk to you.
How you'll make 10x impact:
In this role you will...
  • Drive the evolution of internal optimization engines to support the transition to high-renewable energy grids.
  • Act as a technical bridge between theoretical research and high-performance software execution.
  • Identify and resolve computational bottlenecks in large-scale grid simulations to enable real-time decision-making.
  • Lead the architectural design of scalable solvers that can handle the complexity of modern, decentralized energy resources.
  • Work with power system and software engineering experts on the design and creation of advanced grid optimization tools such as ACOPF, SCED, and SCUC.

What you should have:
  • Master or PhD in a STEM field (such as Operations Research, Electrical Engineering, Computer Science, Physics, Mathematics, or a related field).
  • A strong interest in grid computations, particularly regarding optimization algorithms.
  • Demonstrated proficiency in power systems core concepts.
  • Significant background in the development of optimization software tools.
  • At least 6 years of professional experience focused on modeling and optimization principles.
  • Experience in one or more general-purpose programming languages such as Python, Java, or C/C++.
  • Deep understanding of numerical methods and convex/non-convex optimization solver technologies.
  • Proven ability to translate complex mathematical formulations into maintainable, production-ready code.
  • Strong collaborative skills to work across multi-disciplinary teams of AI researchers and hardware engineers.

It'd be great if you had these:
  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Experience performing sensitivity analysis and security assessments on large-scale power flow models.
  • Familiarity with electricity power markets and grid operations.
  • Skilled and efficient in scientific programming languages (e.g., JAX, Julia, C++, etc.).
  • Familiarity with Machine Learning concepts.

Our values
  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Purpose in everything: We build solutions that solve real problems and create meaningful impact.
  • Stronger together: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer
A culture that supports growth, ownership, and meaningful impact, along with:
  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $207,000 - $300,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
An Equal Opportunity Workplace
At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need that requires accommodation, please contact us at x-accommodation-request@x.team .

Apply