Optimization Engineer Jobs
Optimization Engineer jobs are open across manufacturing, logistics, software, and operations, with specializations in process optimization, supply chain modeling, and algorithmic systems, from entry-level analyst roles to principal and staff engineer positions. See the openings below and apply to the ones that match your experience.
Find Optimization Engineer JobsLooking for remote work? View remote optimization engineer jobs →Student or new grad? View optimization engineer internships →Overview
Showing 5 of 183+ Optimization Engineer jobs
Senior Deployment Engineer - LLM Inference & Optimization
We're looking for a Deployment Engineer who combines hands-on AI engineering, model optimization, and strong customer-facing skills.
You'll work directly with customers to bring AI models and applications into production, improve their performance, and integrate them with enterprise systems. You'll own technical delivery from discovery and benchmarking through deployment and adoption, working closely with customer stakeholders and our product and engineering teams.
This role requires someone who enjoys writing code, experimenting with models, diagnosing performance bottlenecks, and helping customers achieve measurable improvements in model quality, latency, throughput, and cost.
What you'll do
- Understand customer requirements: Lead technical discovery to define use cases, workloads, infrastructure constraints, and targets for model quality, latency, throughput, and cost.
- Optimize inference: Apply techniques such as quantization, batching, prefix caching, KV-cache optimization, and parallelism to improve performance while preserving output quality.
- Adapt models to customer needs: Improve results through prompt optimization, retrieval-augmented generation, and fine-tuning where appropriate. Evaluate the impact of each approach.
- Troubleshoot performance: Investigate issues across model execution, GPU utilization, memory consumption, serving infrastructure, and application behavior.
- Lead technical customer engagement: Run workshops, present benchmark findings, explain tradeoffs, and guide customers through deployment and optimization decisions.
- Build reusable capabilities: Create evaluation tools, benchmark harnesses, deployment configurations, and runbooks. Bring recurring customer needs and performance findings back to product and engineering.
What you'll bring
- 5+ years of experience in software engineering, ML engineering, AI infrastructure, or a related hands-on technical role.
- Strong Python programming skills and experience with frameworks such as PyTorch, Hugging Face Transformers, or comparable tools.
- Hands-on experience deploying and optimizing AI models in production, particularly LLMs.
- Experience with model-serving frameworks such as vLLM, SGLang, TensorRT-LLM, or similar technologies.
- An understanding of GPU memory constraints, numerical precision, batching, caching, and parallelism, including how these affect inference performance.
- Experience building evaluations and benchmarks to measure model quality, latency, throughput, and resource efficiency.
- Experience developing APIs and integrating model endpoints with production applications and customer data systems.
- Familiarity with GPU-based cloud environments, containers, and monitoring tools used to operate model deployments.
- The ability to work directly with customers, communicate technical tradeoffs clearly, and translate business requirements into measurable engineering targets.
- Strong ownership and troubleshooting skills, with the ability to move from an ambiguous problem to a tested solution.
Nice to have
- Experience with parameter-efficient fine-tuning techniques such as LoRA or QLoRA.
- Experience with speculative decoding, multi-GPU inference, or distributed model serving.
- Experience profiling GPU workloads using CUDA, NVIDIA Nsight, or related tools.
- Experience optimizing embedding models, rerankers, vision models, or multimodal systems.
- Experience improving retrieval quality and evaluating end-to-end RAG applications.
- Contributions to open-source model-serving, optimization, or evaluation projects.
- Experience delivering enterprise AI implementations or customer-facing technical engagements.
What success looks like
You help customers deploy AI solutions that meet agreed quality and performance targets. Your work produces measurable improvements in latency, throughput, GPU utilization, and cost while maintaining model quality. Customers understand the tradeoffs, trust your technical guidance, and can operate the solutions you deliver. Your findings and tools make future deployments faster and more effective.
What We Offer
In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
California Applicants
California Consumer Privacy Act
Equal Opportunity & Accommodations
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to technology and/or source code subject to U.S. export control laws. Any such access will be provided only in compliance with applicable U.S. export control requirements. As part of the recruitment process, CoreWeave may request limited information reasonably necessary to assess applicable export-control requirements.
Senior Deployment Engineer - LLM Inference & Optimization
We're looking for a Deployment Engineer who combines hands-on AI engineering, model optimization, and strong customer-facing skills.
You'll work directly with customers to bring AI models and applications into production, improve their performance, and integrate them with enterprise systems. You'll own technical delivery from discovery and benchmarking through deployment and adoption, working closely with customer stakeholders and our product and engineering teams.
This role requires someone who enjoys writing code, experimenting with models, diagnosing performance bottlenecks, and helping customers achieve measurable improvements in model quality, latency, throughput, and cost.
What you'll do
- Understand customer requirements: Lead technical discovery to define use cases, workloads, infrastructure constraints, and targets for model quality, latency, throughput, and cost.
- Optimize inference: Apply techniques such as quantization, batching, prefix caching, KV-cache optimization, and parallelism to improve performance while preserving output quality.
- Adapt models to customer needs: Improve results through prompt optimization, retrieval-augmented generation, and fine-tuning where appropriate. Evaluate the impact of each approach.
- Troubleshoot performance: Investigate issues across model execution, GPU utilization, memory consumption, serving infrastructure, and application behavior.
- Lead technical customer engagement: Run workshops, present benchmark findings, explain tradeoffs, and guide customers through deployment and optimization decisions.
- Build reusable capabilities: Create evaluation tools, benchmark harnesses, deployment configurations, and runbooks. Bring recurring customer needs and performance findings back to product and engineering.
What you'll bring
- 5+ years of experience in software engineering, ML engineering, AI infrastructure, or a related hands-on technical role.
- Strong Python programming skills and experience with frameworks such as PyTorch, Hugging Face Transformers, or comparable tools.
- Hands-on experience deploying and optimizing AI models in production, particularly LLMs.
- Experience with model-serving frameworks such as vLLM, SGLang, TensorRT-LLM, or similar technologies.
- An understanding of GPU memory constraints, numerical precision, batching, caching, and parallelism, including how these affect inference performance.
- Experience building evaluations and benchmarks to measure model quality, latency, throughput, and resource efficiency.
- Experience developing APIs and integrating model endpoints with production applications and customer data systems.
- Familiarity with GPU-based cloud environments, containers, and monitoring tools used to operate model deployments.
- The ability to work directly with customers, communicate technical tradeoffs clearly, and translate business requirements into measurable engineering targets.
- Strong ownership and troubleshooting skills, with the ability to move from an ambiguous problem to a tested solution.
Nice to have
- Experience with parameter-efficient fine-tuning techniques such as LoRA or QLoRA.
- Experience with speculative decoding, multi-GPU inference, or distributed model serving.
- Experience profiling GPU workloads using CUDA, NVIDIA Nsight, or related tools.
- Experience optimizing embedding models, rerankers, vision models, or multimodal systems.
- Experience improving retrieval quality and evaluating end-to-end RAG applications.
- Contributions to open-source model-serving, optimization, or evaluation projects.
- Experience delivering enterprise AI implementations or customer-facing technical engagements.
What success looks like
You help customers deploy AI solutions that meet agreed quality and performance targets. Your work produces measurable improvements in latency, throughput, GPU utilization, and cost while maintaining model quality. Customers understand the tradeoffs, trust your technical guidance, and can operate the solutions you deliver. Your findings and tools make future deployments faster and more effective.
What We Offer
In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include:
- Medical, dental, and vision insurance - 100% paid for by CoreWeave
- Company-paid Life Insurance
- Voluntary supplemental life insurance
- Short and long-term disability insurance
- Flexible Spending Account
- Health Savings Account
- Tuition Reimbursement
- Ability to Participate in Employee Stock Purchase Program (ESPP)
- Mental Wellness Benefits through Spring Health
- Family-Forming support provided by Carrot
- Paid Parental Leave
- Flexible, full-service childcare support with Kinside
- 401(k) with a generous employer match
- Flexible PTO
- Catered lunch each day in our office and data center locations
- A casual work environment
- A work culture focused on innovative disruption
California Applicants
California Consumer Privacy Act
Equal Opportunity & Accommodations
CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.
As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com.
Export Control Compliance
This position requires access to technology and/or source code subject to U.S. export control laws. Any such access will be provided only in compliance with applicable U.S. export control requirements. As part of the recruitment process, CoreWeave may request limited information reasonably necessary to assess applicable export-control requirements.
Optimization Engineer Jobs by Experience Level
See All 183+ Optimization Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Optimization Engineer JobsOptimization Engineer Job Market
Who's Hiring
- Apple19
- Packaging Corporation of America11
- Meta9
- Zoox7
- Stiles Machinery7
Top Industries Hiring
- Distribution & Wholesale
- Automotive
- Technology & Software
- Electronics & Hardware
- Artificial Intelligence
What Employers Look For
The qualifications that appear most often in optimization engineer jobs.
- Bachelor's or master's degree in industrial engineering, operations research, or a related field
- Proficiency in Python or a similar language for modeling and data analysis
- Experience with mathematical programming solvers such as Gurobi, CPLEX, or OR-Tools
- Ability to formulate and solve linear, nonlinear, or mixed-integer programming problems
- Familiarity with simulation tools and statistical analysis methods
- 2 or more years of applied experience in process improvement, supply chain, or algorithmic optimization
Tips for Your Optimization Engineer Job Search
Quantify every optimization outcome on your resume
Hiring managers for these roles expect numbers. Replace vague phrases like 'improved efficiency' with specific metrics: cycle time reductions, cost savings, or throughput gains your models or process changes delivered. Generic impact statements won't pass technical screening.
List your solver and modeling tools explicitly
Job postings for optimization engineers often screen for specific tools like Gurobi, CPLEX, OR-Tools, or Pyomo. If you've used any of these, name them in your skills section and in the context of a real project, not just as a list.
Apply early to roles that fit
Migrate Mate lists optimization engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings that match your domain depth
Optimization engineering is applied very differently in supply chain, semiconductor manufacturing, and software systems. Filter openings by domain so your resume's examples align tightly with what the team actually works on, rather than sending a generalist application.
Prepare a whiteboard session for integer programming
Many technical interviews include a live problem involving constraints and an objective function. Practice formulating a small mixed-integer or linear programming problem from scratch, explaining your variable definitions and trade-offs out loud as you go.
Negotiate scope alongside compensation
Optimization roles vary widely in autonomy: some are model-building only, others own end-to-end deployment. Before accepting, ask directly whether you'll be implementing solutions in production or handing off to an engineering team, since this shapes your long-term growth.
Optimization Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most optimization engineers?
The most active employers for optimization engineers right now are Apple, Packaging Corporation of America, and Meta, and the most openings are in California, Texas, and Washington, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated in logistics, semiconductor, and enterprise software companies.
How many optimization engineer jobs are remote?
About 45% of optimization engineer openings are fully remote or hybrid as of November 2026, with remote work most common in roles focused on algorithmic modeling and software-side optimization rather than on-site manufacturing or physical process engineering.
How do you become an optimization engineer?
Start with a degree in industrial engineering, operations research, mathematics, or computer science, then build hands-on experience with mathematical modeling and a solver library. Develop projects that demonstrate formulating a real constraint problem and solving it programmatically. Many engineers move into the role from adjacent positions in data science, supply chain analysis, or systems engineering by taking on optimization-specific projects and building a portfolio of concrete, measurable outcomes.
Can you get hired as an optimization engineer with little experience?
Yes, entry-level positions exist, particularly at companies with structured engineering rotations or in process improvement roles. The key is demonstrating that you can formulate a problem mathematically and implement a solution, even if the example comes from a class project, internship, or self-directed work. Employers in manufacturing and logistics often hire graduates who show modeling fundamentals and a willingness to learn domain-specific constraints on the job.
What does the optimization engineer interview process look like?
Most processes include a recruiter screen, a technical phone interview covering modeling concepts or coding, and a final round with a live problem-solving session. You'll typically be asked to formulate an optimization problem from a business description, define variables and constraints, and discuss trade-offs in your approach. Some companies also include a take-home case study or a presentation of a past project where you explain your methodology and results.
Where can I find and apply to optimization engineer jobs?
You can find and apply to optimization engineer jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that fit your specialization and experience level, then apply directly to each listing that matches what you're looking for.
See All 183+ Optimization Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Optimization Engineer Jobs