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Remote Rf Optimization Engineer Jobs in Los Angeles, CA

Future Engineers, LLC

Sr. Software Engineer

Burbank, CA · Remote

$80 - $120/hr

Platform optimization and load time optimization * Ability to interface with front-end developers ... This is a remote position and anticipated to be 10-20 hours per week. Only US-based developers will ...

Turnblock.io

Technical Lead Remote (Web3)

Los Angeles, CA · Remote

$100K - $250K/yr

... engineers and a Technical Product Manager. * Oversee the design, implementation, and optimization ... Fully Remote Work Environment * Opportunities for Career Growth * Collaborative Team of Top-Tier ...

Eitacies Inc

Senior Data Engineer

Los Angeles, CA · Remote

$60/hr

Senior Data Engineer (Level II & Level III) Level II is Remote work Level III is Onsite at Los ... optimization, along with strong collaboration across onsite and offshore teams. Key ...

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Remote Rf Optimization Engineer information

See Los Angeles, CA salary details

$39.9K

$126.8K

$197.2K

How much do remote rf optimization engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for remote rf optimization engineer in Los Angeles, CA is $126,802.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,100.00 and $149,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote RF Optimization Engineer, and why are they important?

To thrive as a Remote RF Optimization Engineer, you need a solid background in wireless communication principles, network optimization, and a degree in electrical or telecommunications engineering. Familiarity with RF planning tools (such as Atoll, Actix, or TEMS), drive test equipment, and certifications like CCNA or relevant vendor-specific credentials are highly valued. Strong analytical thinking, problem-solving abilities, and effective remote communication skills set top performers apart in this role. These skills ensure optimal network performance, efficient troubleshooting, and seamless collaboration on distributed engineering teams.

What are some common challenges faced by Remote RF Optimization Engineers, and how can they be addressed?

Remote RF Optimization Engineers often encounter challenges such as limited on-site access, coordinating with field teams, and troubleshooting network issues without direct physical observation. These challenges can be addressed by leveraging advanced remote monitoring tools, maintaining clear communication channels with local technicians, and utilizing simulation software to analyze and resolve signal problems. Building strong relationships with cross-functional teams and staying updated on the latest industry best practices also help in effectively managing remote optimization tasks.

What is a Remote RF Optimization Engineer?

A Remote RF Optimization Engineer is a telecommunications professional who specializes in analyzing, optimizing, and improving the performance of wireless radio frequency (RF) networks from a remote location. Their main tasks include monitoring network KPIs, troubleshooting interference or coverage issues, and implementing solutions to enhance signal quality and capacity. Working remotely, they use specialized software tools to access, analyze, and optimize cellular networks such as LTE, 5G, or Wi-Fi, ensuring reliable communication services for users.

What is the difference between Remote Rf Optimization Engineer vs Remote Wireless Network Engineer?

AspectRemote Rf Optimization Engineer

The Remote Rf Optimization Engineer focuses on optimizing radio frequency performance for wireless networks, primarily working on signal quality, interference reduction, and network efficiency. The Remote Wireless Network Engineer also works on wireless systems but has a broader scope, including network design, deployment, and troubleshooting of entire wireless infrastructures. Both roles require knowledge of RF principles and certifications like CWNP, but the Optimization Engineer emphasizes fine-tuning existing networks, while the Network Engineer handles overall network setup and maintenance.

What are popular job titles related to Remote Rf Optimization Engineer jobs in Los Angeles, CA? For Remote Rf Optimization Engineer jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Remote Rf Optimization Engineer jobs in Los Angeles, CA look for? The top searched job categories for Remote Rf Optimization Engineer jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Remote Rf Optimization Engineer jobs? Cities near Los Angeles, CA with the most Remote Rf Optimization Engineer job openings:
Remote Rf Optimization Engineer jobs near you

Software Engineer, Finite Element Analysis & Structural Optimization

InfinitForm, Inc

Los Angeles, CA • On-site, Remote

Full-time

Posted 11 days ago

Job description

Full-time | Hybrid (LA / Orange County) or Remote
About InfinitForm
InfinitForm is building the Physical AI platform for engineering teams.
We help manufacturers generate production-ready designs dramatically faster by bringing simulation, optimization, manufacturability constraints, and editable parametric CAD into one workflow.
Today, engineering teams often spend months moving from concept to validated, manufacturable design. InfinitForm compresses that cycle from months to days - helping teams explore more design options, reduce late-stage rework, and bring better physical products to production faster.
Our platform is designed for aerospace, automotive, defense, robotics, and advanced manufacturing companies operating at the frontier of physical product development.
Backed by leading investors and built by pioneers in computational geometry, simulation, and advanced manufacturing, InfinitForm is defining a new category at the intersection of AI and engineering.
The Role
We're looking for a skilled and driven Finite Element Analysis & Structural Optimization Engineer to join our core engineering team. The seniority level for this role is flexible.
You'll work at the intersection of computational mechanics, simulation, optimization, and AI-native engineering workflows - helping build the core simulation and optimization infrastructure behind InfinitForm's platform.
This is a deeply technical, hands-on role focused on building high-performance systems for structural simulation and generative engineering. Your work will directly shape the algorithms and solvers powering a new generation of engineering software for the physical world.
You'll collaborate closely with researchers, computational engineers, geometry engineers, and product teams working on complex real-world problems across aerospace, automotive, defense, robotics, and industrial manufacturing.
What You'll Do
Simulation & Solver Development
  • Design, implement, and optimize finite element analysis (FEA) solvers and structural simulation pipelines
  • Develop high-performance simulation infrastructure for large-scale engineering optimization workflows
  • Improve solver stability, accuracy, scalability, and runtime performance
  • Build production-quality numerical software in C++ for scientific and engineering computation
  • Contribute to GPU-accelerated simulation and optimization systems
Structural Optimization & Research
  • Develop structural optimization algorithms including topology, shape, and sizing optimization
  • Work on sensitivity analysis, constraint handling, and optimization methodologies
  • Explore new approaches to simulation-aware and manufacturability-aware optimization
  • Contribute to research-oriented problem solving across engineering and computational geometry domains
  • Help bridge optimization outputs into production-ready CAD workflows
Technical Collaboration
  • Collaborate closely with Product, Research, and Application Engineering teams
  • Participate in technical architecture discussions, code reviews, and solver design decisions
  • Document technical findings and communicate complex ideas clearly across the team
  • Help shape the technical direction of InfinitForm's core engineering platform
What Success Looks Like
  • Meaningful improvements in optimization quality, manufacturability, and runtime performance
  • Technical contributions that directly improve customer outcomes and platform capability
  • Strong collaboration between simulation, geometry, and product engineering teams

What You'll Bring
  • MS or PhD in Mechanical Engineering, Aerospace Engineering, Applied Mathematics, Physics, Computational Mechanics, Computer Science, or a related technical field, with a focus on FEA, structural optimization, numerical methods, simulation, or scientific computing
  • Strong foundation in finite element analysis, solid mechanics, and numerical methods
  • Deep understanding of structural optimization techniques including topology optimization and sensitivity analysis
  • Strong C++ experience for scientific, numerical, or high-performance computing applications
  • Strong mathematical and problem-solving skills
  • Ability to work independently on complex technical systems
  • Collaborative mindset and ability to communicate technical ideas clearly
  • Curiosity and excitement for solving difficult engineering and computational problems
Nice to Have
  • Experience with GPU computing (CUDA, OpenCL, or similar)
  • Familiarity with parallel computing or HPC environments
  • Background in computational geometry, CAD/CAE systems, or generative design
  • Experience with large-scale numerical optimization systems
  • Published research or advanced academic background in computational mechanics, simulation, or optimization
  • Experience working on production engineering software platforms

Why InfinitForm
  • Work on foundational technology shaping the future of engineering and manufacturing
  • Solve genuinely difficult computational and optimization problems with real-world impact
  • Work alongside a highly technical team including multiple PhDs across computational geometry, simulation, optimization, AI/ML, and advanced manufacturing
  • Help define a new category at the intersection of AI and engineering
  • Competitive compensation and meaningful equity

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