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Home Based Convex Optimization Jobs (NOW HIRING)

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

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.

Vise

Quantitative Engineer

New York, NY · On-site

$190K - $270K/yr

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 ...

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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 Jul 10, 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 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.

What is a Home Based Convex Optimization job?

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.
More about Home Based Convex Optimization jobs
What cities are hiring for Home Based Convex Optimization jobs? Cities with the most Home Based 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 Home Based Convex Optimization jobs? States with the most job openings for Home Based Convex Optimization jobs include:
What job categories do people searching Home Based Convex Optimization jobs look for? The top searched job categories for Home Based Convex Optimization jobs are:
Home Based Convex Optimization jobs near you
Infographic showing various Home Based Convex Optimization job openings in the United States as of July 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.
Senior Motion Planning Engineer - Trajectory Optimization

Senior Motion Planning Engineer - Trajectory Optimization

Torc Robotics

Ann Arbor, MI • On-site, Remote

$119K - $158K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
Join Torc's Behaviors Team, where we develop the planning, prediction, and decision-making systems that determine how our autonomous trucks navigate the world safely, efficiently, and predictably. Our team operates at the intersection of robotics, machine learning, optimization, simulation, and safety, building the core autonomy capabilities that translate perception into action.
We are seeking a Senior Software Engineer who is passionate about solving challenging autonomy problems and building production-quality software for real-world autonomous systems. This role is focused on motion planning, trajectory generation, and trajectory optimization for autonomous tractor-trailer vehicles. You will contribute directly to the design, development, validation, and deployment of planning capabilities that enable safe and reliable autonomous driving. You will work closely with engineers across autonomy, controls, simulation, safety, and validation to help deliver robust autonomy behaviors at scale.
What You'll Do
  • Design, develop, and optimize motion planning algorithms including trajectory generation, trajectory selection, behavior planning, and optimization-based planning approaches for autonomous trucks.
  • Develop planning solutions leveraging techniques such as graph search, sampling-based planning, optimization-based planning, spline/B-spline trajectories, convex optimization, and Frenet-frame approaches.
  • Incorporate vehicle kinematic and dynamic constraints into planning systems to ensure safe, feasible, and comfortable vehicle behavior.
  • Develop production-quality software using modern C++ within a Linux environment while adhering to quality, safety, testing, and deployment best practices.
  • Participate in software architecture discussions and contribute to technical designs that support scalable and maintainable autonomy systems.
  • Develop and execute validation strategies across Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), and Vehicle-in-the-Loop (ViL) environments.
  • Collaborate closely with Safety, Controls, Perception, Validation, and Simulation teams to develop safe and reliable autonomous driving behaviors.
  • Investigate and debug vehicle behavior by reproducing issues in simulation, analyzing system performance, and implementing software improvements.
  • Support vehicle integration, deployment activities, and post-deployment investigations to ensure reliable autonomy performance.
  • Participate in technical design reviews, code reviews, and continuous improvement initiatives across the Behaviors organization.
  • Mentor junior engineers through collaboration, technical guidance, and knowledge sharing.

What You'll Need to Succeed
  • Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field with 5+ years of industry experience; OR Master's degree with 3+ years of experience; OR PhD with 1+ years of experience.
  • Strong proficiency in modern C++ development within Linux-based environments.
  • Experience developing robotics, autonomous vehicle, ADAS, or other complex real-time software systems.
  • Strong experience developing motion planning, trajectory generation, trajectory optimization, behavior planning, or decision-making systems for robotics or autonomous systems.
  • Solid understanding of vehicle dynamics, vehicle kinematics, trajectory feasibility, and planning system architecture.
  • Strong foundation in linear algebra, numerical optimization, geometry, and robotics algorithms.
  • Strong understanding of software engineering fundamentals, system design principles, and scalable development practices.
  • Experience working across the full software development lifecycle, from design and implementation through validation, deployment, and operational support.
  • Strong problem-solving skills and the ability to debug complex system-level issues.
  • Excellent communication and collaboration skills within cross-functional engineering teams.
  • Ability to work independently while contributing effectively within a highly collaborative environment.

Bonus Points!
  • Experience with motion planning, trajectory optimization, behavior prediction, or decision-making systems for autonomous vehicles.
  • Experience with Model Predictive Control (MPC), convex optimization, quadratic programming (QP), nonlinear optimization, or other optimization-based planning techniques.
  • Experience applying machine learning techniques such as imitation learning, reinforcement learning, or hybrid planning architectures.
  • Understanding of vehicle dynamics, controls, state estimation, and trajectory tracking.
  • Experience developing software in both C++ and Python environments.
  • Experience integrating machine learning models into real-time or production systems.
  • Experience working with simulation platforms and large-scale autonomy validation environments.
  • Experience with robotics frameworks such as ROS/ROS2, Autoware, Apollo, or similar autonomy platforms.
  • Exposure to CUDA, GPU acceleration, TensorRT, or high-performance compute environments.
  • Experience supporting on-vehicle testing, debugging, and deployment activities.
  • Passion for autonomous vehicles, robotics, and solving complex real-world engineering challenges.

Work Location: For this position, we are open to hiring in Ann Arbor, MI, Blacksburg, VA, Fort Worth, TX office work locations in a hybrid capacity. We are also open to hiring Remote in the United States & Canada
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102795
Hiring Range for Job Opening
US Pay Range
$160,800-$193,000 USD

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