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Physics Informed Machine Learning Jobs in Berkeley, CA

SirenOpt

Lead Software Engineer

San Leandro, CA · On-site

Using a novel combination of cold atmospheric plasma, physics-informed machine learning, and predictive analytics, SirenOpt creates unique, real-time fingerprints that capture material signals no ...

Workday

Machine Learning Engineer III

Pleasanton, CA

Bachelor's (Master's or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent * 3+ yrs experience as a member of a data science, machine learning engineering, or ...

Jobzhr

Machine Learning Engineer III

Pleasanton, CA · On-site

$160 - $240/hr

Bachelor's (Master's or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent * 3+ yrs experience as a member of a data science, machine learning engineering, or ...

Adobe

Senior Machine Learning Engineer

San Francisco, CA

$172K - $306K/yr

A degree in computer science, statistics, operations research, applied physics, engineering, or a ... machine learning. Together, we'll develop groundbreaking solutions that empower creatives around ...

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How much do physics informed machine learning jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for physics informed machine learning in Berkeley, CA is $24.57, according to ZipRecruiter salary data. Most workers in this role earn between $15.29 and $31.20 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Berkeley, CA?

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The top searched job categories for Physics Informed Machine Learning jobs in Berkeley, CA are:

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Cities near Berkeley, CA with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Berkeley, CA as of August 2026, with employment types broken down into 6% Internship, 44% Full Time, 43% Part Time, and 7% Contract. Highlights an 100% In-person job distribution, with an average salary of $51,097 per year, or $24.6 per hour.

Staff Electrical Engineer - FPGA / MPSoC Systems & Digital Signal Processing

SirenOpt

San Leandro, CA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago

Job description

About SirenOpt
SirenOpt helps manufacturers make better, safer, and more reliable micro- and nano-materials. These materials are the building blocks of critical sectors of the global economy such as batteries, computer chips, aircraft components, and power systems. But, surging material demand and growing complexity are pushing production to unprecedented scales and speeds, leaving manufacturers effectively flying blind. Small, undetected variations during production lead to wastage, lower performance, higher costs, and safety risks.
SirenOpt is changing this. Our manufacturing intelligence platform scans materials, revealing critical internal information without damaging them. Using a novel combination of cold atmospheric plasma, physics-informed machine learning, and predictive analytics, SirenOpt creates unique, real-time fingerprints that capture material signals no other method can access. These insights give manufacturers unprecedented visibility into how materials behave as they are made.
We turn hidden data into actionable intelligence to help manufacturers reduce variability and thus increase yield and performance. The technology can be deployed as a standalone tool or integrated directly into factory production lines. SirenOpt is currently deploying early versions of its platform with some of the largest industrial manufacturers in the world across North America, Europe, and Asia. Our first commercial product will be released in 2026.
Role Overview
SirenOpt is looking for a Staff Electrical Engineer - FPGA / MPSoC & Digital Signal Processing Systems to lead the architecture, design, implementation, and validation of high-performance programmable logic, embedded processing, and FPGA-based digital signal processing systems powering our next-generation metrology platform.
This is a hands-on, high-impact role for someone who enjoys working close to the technology, solving hard problems quickly, and helping shape products in an early-stage startup environment.
This role is ideal for an engineer who is energized by deep tech, thrives in cross-functional environments, and is motivated by the opportunity to build something genuinely new.
You will work closely with a small, highly capable team to turn advanced sensing, digital signal processing, and control concepts into robust, high-performance, field-ready systems.
What You'll Do
  • Lead the architecture, design, implementation, and validation of FPGA, MPSoC, and FPGA-based digital signal processing systems for SirenOpt's metrology platform.
  • Develop designs from concept through architecture definition, RTL development, modeling, simulation, verification, testbench development, bench testing, and system bring-up.
  • Build and maintain robust simulation and verification environments to validate functionality, timing, performance, and reliability at both block and system levels.
  • Design and implement FPGA-based digital signal processing pipelines for real-time sensing and metrology applications, including FIR filters, synchronization pipelines, control loops, and low-latency data paths.
  • Implement, evaluate, and refine signal-processing and control algorithms such as PID, ADPLL, filtering, and signal-conditioning methods for high-performance measurement systems.
  • Use MATLAB and Python for algorithm development, modeling, data analysis, system validation, and signal and electrical data characterization.
  • Perform large-scale data analysis to evaluate signal quality, characterize system behavior, and guide design tradeoffs and performance optimization.
  • Collaborate closely with hardware, electrical, software, algorithm, and systems engineers to support end-to-end FPGA, MPSoC, firmware, and hardware integration.
  • Read and interpret schematics to understand board-level architecture, interfaces, signal paths, power domains, and subsystem dependencies.
  • Bring up new boards in the lab, troubleshoot issues independently, and debug hardware/firmware interactions using oscilloscopes, logic analyzers, signal generators, power supplies, and related lab equipment.
  • Help translate frontier R&D concepts into scalable, reliable, and manufacturable digital systems.

What We're Looking For
  • B.S., M.S., or PhD in Electrical Engineering, Computer Engineering, or a related field, with 5+ years of relevant industry experience.
  • Strong experience with end-to-end FPGA and MPSoC design, including architecture, RTL development, simulation, synthesis, timing closure, verification, and board bring-up.
  • Advanced experience with FPGA-based digital signal processing for real-time systems, including FIR filters, synchronization methods, streaming pipelines, and control-oriented digital design.
  • Strong experience with algorithm modeling and analysis using MATLAB and Python.
  • Experience implementing and validating signal-processing and control techniques such as PID, ADPLL, filtering, and signal characterization workflows.
  • Strong command of HDL/RTL implementation for digital signal processing, control, and high-performance data-path design.
  • Hands-on experience developing testbenches, verification environments, and bench-level validation workflows.
  • Strong understanding of firmware/hardware integration and system-level debugging in tightly coupled digital platforms.
  • Ability to read and understand electrical schematics and work effectively at the board and subsystem level.
  • Proven experience troubleshooting and bringing up hardware in the lab using standard electrical test equipment.
  • Experience working in a fast-moving, multidisciplinary environment with a high degree of ownership and technical independence.
  • Strong communication skills and a practical, problem-solving mindset.

Nice to Have
  • Experience providing technical leadership for hardware and firmware engineering teams in complex product development environments.
  • Experience with image processing or vision-related algorithm pipelines.
  • PCB design experience, including familiarity with board-level layout considerations and signal integrity tradeoffs.
  • Experience with high-speed interfaces, instrumentation systems, or real-time sensing platforms.
  • Familiarity with mixed-signal systems and integration with ADCs, DACs, sensors, and embedded processors.
  • Exposure to metrology systems, scientific instrumentation, or advanced materials applications.

Why Join SirenOpt
  • Help define a new category in advanced materials metrology.
  • Work on genuinely novel deep-tech hardware with real scientific and industrial impact.
  • Join an early-stage team where your decisions directly shape the product, technology, and company.
  • Build systems at the intersection of plasma science, electronics, sensing, AI-driven analytics, programmable logic, and advanced digital signal processing.
  • Contribute to technology that can expand what researchers and industry teams are able to see, measure, and optimize.

Actual compensation within the pay range listed will be decided based on factors including skills and prior relevant experience.
Base Pay Range
$160,000-$240,000 USD
Benefits
  • Equity and Salary compensation depends on experience
  • Health, Dental, Vision plans provided
  • 401k matching provided
  • Time off: 20 days of PTO per year, plus approximately 15 paid US holidays per year

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