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Embedded Machine Learning Engineer Jobs in Los Angeles, CA

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Turion Space

Machine Learning Engineer

Irvine, CA · On-site

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions for computer vision problems * Proficient with at least one major ...

Bespoke Labs

Machine Learning Engineer

Northridge, CA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Los Angeles, CA

Embedded Machine Learning Engineer information

See Los Angeles, CA salary details

$75.4K

$165.3K

$187.5K

How much do embedded machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for embedded machine learning engineer in Los Angeles, CA is $165,272.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,700.00 and $186,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

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

Staff Machine Learning Engineer

Prodege LLC

El Segundo, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, PTO

Posted 12 days ago

Job description

Job Description:
Read this part first:
This is a role for someone who wants to solve hard machine learning problems by building production systems that matter.
We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes.
This is a deeply hands-on individual contributor role. You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level.
If you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you.
You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.
Prodege:
A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.
As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!
What you'll own
  • Design, build, and operate production machine learning systems from development through deployment
  • Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization
  • Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement
  • Reliable production ML practices including testing, observability, retraining, and model health
  • Technical leadership through code reviews, collaboration, and mentoring less experienced engineers
  • Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems

What makes this role exciting
  • You'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.
  • You'll own production systems-not just models-from experimentation through deployment and optimization.
  • You'll build on top of a production platform processing 50M daily events, 500M daily pipeline records, and a 100TB Iceberg lake.
  • You'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.
  • You'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.
  • You'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.

What you'll do
  • Design, build, deploy, and maintain production machine learning systems.
  • Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.
  • Improve feature engineering, model performance, inference latency, and operational reliability.
  • Design and analyze offline evaluations and A/B experiments to validate business impact.
  • Partner with Data Engineering to build reliable data pipelines and feature sets for ML.
  • Contribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management.
  • Review code, mentor teammates, and help raise engineering quality across the ML organization.
  • Leverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation.

What you'll bring (must-haves)
  • 6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields.
  • 3+ years building, deploying, and operating production machine learning systems.
  • Strong experience building production recommendation, ranking, personalization, optimization, or prediction systems.
  • Experience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains.
  • Strong understanding of:
    • Feature engineering
    • Offline and online inference
    • Experimentation and A/B testing
    • Model serving
    • Monitoring and retraining
    • MLOps best practices
  • Experience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes.
  • Strong software engineering fundamentals with excellent coding skills.
  • Comfort operating in ambiguous environments while independently driving technical solutions.
  • Demonstrated ability to mentor engineers and influence technical decisions across teams.

Bonus points
  • Experience with ROAS optimization, bidding systems, rewards platforms, or monetization models.
  • Experience with streaming or near-real-time ML systems.
  • Experience with recommendation engines or personalization at scale.
  • Experience using feature stores or shared ML infrastructure.
  • Experience with causal inference, uplift modeling, or counterfactual reasoning.
  • Master's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline.
  • Experience using AI-assisted development tools in software engineering workflows.

Pay Transparency:
The anticipated base salary range for this position is $240,000 to $290,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
Prodege Benefits:
Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.
Equal Employment Opportunity Statement
At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.
FCIHO
Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.

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