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Home Based Convex Optimization Jobs (NOW HIRING)

Gridmatic Inc

Power Systems Research Scientist

Cupertino, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Understanding of numerical methods for convex and/or non-convex optimization * Strong programming ... through Millie - Home Office Stipend Protecting your future for you and your family: - 401K ...

Federato Technologies

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

Company Description Federato Technologies is a Series A startup based in San Fransisco, CA looking ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

Federato Technologies

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

Company Description Federato Technologies is a Series A startup based in San Fransisco, CA looking ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

Vise

Quantitative Engineer

New York, NY · On-site

$190K - $270K/yr

  • Medical

  • Retirement

  • PTO

We work closely with convex optimization techniques and numerical optimizations of various problems ... Your actual compensation will be determined based on your skills, qualifications, and experience.

SpaceX

Software Engineer (Starlink Mobile)

Redmond, WA · On-site

$149K - $187K/yr

... satellite-based global network to connect mobile phones and maximize user experience • ... or convex optimization • Developed, debugged, and deployed software that has been used in real ...

Vise

Quantitative Engineer

New York, NY

$190K - $270K/yr

  • Medical

  • Retirement

  • PTO

We work closely with convex optimization techniques and numerical optimizations of various problems ... Your actual compensation will be determined based on your skills, qualifications, and experience.

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Home Based Convex Optimization information

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$16K

$55.8K

$102K

How much do home based convex optimization jobs pay per year?

As of Aug 20, 2026, the average yearly pay for home based 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 a home based convex optimization?

A Home Based Convex Optimization job involves working remotely to solve mathematical problems where the objective function is convex, meaning any local minimum is a global minimum. Professionals in this role typically use advanced mathematical and computational techniques to optimize processes, systems, or models across various industries, such as finance, engineering, or machine learning. Tasks may include developing algorithms, implementing optimization models, and analyzing data sets to find optimal solutions. These jobs often require a strong background in mathematics, computer science, and experience with optimization software or programming languages.

What are the key skills and qualifications needed to thrive as a home based convex optimization specialist, and why are they important?

To excel as a Home-Based Convex Optimization Specialist, you need a strong background in mathematics, particularly linear algebra and calculus, along with experience in optimization theory and a relevant degree such as mathematics, engineering, or computer science. Proficiency with technical tools like MATLAB, Python (with libraries such as CVXPY), and optimization solvers is typically required. Critical thinking, problem-solving, and effective remote communication are essential soft skills for success in this independent, analytical role. These skills are crucial for accurately modeling, solving complex optimization problems, and collaborating efficiently with remote teams or clients.

What are some common challenges faced by professionals working in home based convex optimization roles, and how can they be addressed?

One common challenge in home-based convex optimization roles is maintaining effective communication with team members, especially when collaborating on complex mathematical models or sharing large datasets. To address this, professionals often use collaborative tools such as cloud-based platforms and version control systems to facilitate seamless workflow and project tracking. Additionally, the solitary nature of remote work can make problem-solving more difficult, so regular virtual meetings and knowledge-sharing sessions are essential for fostering a supportive team environment. Staying updated with the latest research and optimization software also helps in overcoming technical obstacles and enhancing productivity.

What is the difference between Home Based Convex Optimization vs Data Scientist?

AspectHome Based Convex OptimizationData Scientist
Required CredentialsMathematics, Optimization, Computer Science degreesStatistics, Mathematics, Computer Science degrees
Work EnvironmentRemote, independent work on optimization problemsRemote or office, analyzing data and building models
Industry UsageFinance, tech, research institutionsTech, finance, healthcare, marketing

Home Based Convex Optimization specialists focus on solving mathematical optimization problems remotely, often within research or technical roles. Data Scientists analyze data to extract insights and build predictive models. While both roles require strong analytical skills and related credentials, their core tasks differ: one emphasizes mathematical problem-solving, the other data analysis. They are often searched together due to overlapping skills and remote work options.

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Home Based Convex Optimization jobs near you
Infographic showing various Home Based Convex Optimization job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 14% Part Time, and 7% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Senior Staff Engineer, Autonomous Planning & Optimization (California)

Shield AI

California, MO • On-site

$94K - $128K/yr

Full-time

Posted 2 days ago

New

Job description

Shield AI is seeking a highly experienced expert in optimization and autonomous systems to join the Discrete Planning Group. You will research, design, and implement state-of-the-art algorithms for task allocation, scheduling, and sequencing across heterogeneous autonomous vehicles, while enhancing C++-based mission planning software.

The role requires a PhD or a Masters with strong experience in optimization and operations research, with proficiency in ILP/CP/convex optimization and

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