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Home Based Convex Optimization Jobs (NOW HIRING)

QCi

Senior Engineer, Quantum Algorithms

Hoboken, NJ · On-site

... onto entropy-based photonic quantum processors, including post-processing pipelines. * Build ... Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer ...

QCi

... onto entropy-based photonic quantum processors, including post-processing pipelines. * Build ... Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer ...

Children's Aid

Home-Based Teacher

Bronx, NY · On-site +1

$21.04 - $24.70/hr

The Home-Based Teacher maintains compliance with Head Start Performance Standards, applicable ... Promote high-quality teaching and learning in the home setting that leads to optimal development ...

New

Cellanome

Machine Learning Engineer

Foster, OR · On-site +1

$160K - $215K/yr

This role reports to the Sr. Director AI and can be based in our San Diego CA or Foster City CA ... Familiarity with optimization and estimation techniques such as convex optimization, Kalman ...

pony.ai

Research Intern - Deep Learning

Fremont, CA

$7.0K - $10K/mo

Experience in convex optimization, computational geometry or linear algebra. * Experience in GPU ... This position is rolling based and it can start any time. * This position is fully onsite in ...

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All JobsHome Based Convex Optimization Jobs

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:
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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 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 Software Engineer - Droid

Senior Motion Planning Software Engineer - Droid

Zipline

South San Francisco, CA • On-site

$200K - $245K/yr

Other

Medical, Dental, Vision, PTO

Re-posted 26 days ago

Job description

About 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.

  • 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.

Why Join Now?

  • Impact at scale: Your planner won't benchmark in isolation-it will fly thousands of missions/day delivering essential goods.

  • Technical frontier: Real-time multi-agent autonomy, joint optimization, and robustness under uncertainty at a scale few have seen.

  • Ownership: High-leverage IC role-your decisions shape Zipline's flight stack and the behavior of a global fleet.

  • Category leadership: Help define the standard for safe, reliable autonomous flight in the real world.

 
What Else You Need to Know   
The starting cash range for this role is $200,000 - $245,000; please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. We are always open to negotiation. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more. 
 
Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.
 
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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