Machine Learning Engineer Jobs in Los Angeles, CA
Machine Learning Engineer jobs in Los Angeles are concentrated in Culver City, West Los Angeles, and the Westside tech corridor, driven by demand in entertainment technology, aerospace, and health tech. Companies hiring right now include SentiLink, Whatnot, and Riot Games. See the openings below and apply to the ones that match your experience.
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Showing 5 of 67+ Machine Learning Engineer jobs
INTRODUCTION
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
We’re looking for a Principal Machine Learning Engineer to join the Content ML team at Snap! We build large-scale recommender systems for all of Snap’s video content products.
ROLE AND RESPONSIBILITIES
- Lead the vision and roadmap for Snap’s large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover, and Friend Stories.
- Technically lead a group of talented engineers from Content ML and Platform teams to operate and scale the existing recommender system.
- Work with cross-team ML, Infra, and Research partners to design the next-gen recommender system and incorporate SOTA industry research in recommendation systems, foundation models, multimodal signal understanding, deep user understanding, and related areas. We actively participate in and publish at top-tier conferences.
- Partner with engineers, product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support long-term company priorities.
- Advance the ML tech stack for recommendations, improving scalability, efficiency, reliability, and overall system performance.
- Stay up to date on emerging trends and advancements in the RecSys landscape and proactively identify opportunities to leverage these developments to further enhance Snap’s content capabilities.
- Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.
KNOWLEDGE, SKILLS & ABILITIES
- Deep understanding of RecSys architectures and experience applying them to real-world production systems.
- Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
- Experience leading teams or roadmaps focused on recommendations and/or personalization.
- Ability to design, train, deploy, and optimize state-of-the-art machine learning models for performance, reliability, and scale.
- Excellent programming and software engineering skills, with an emphasis on clean design and production-readiness.
- Ability to quickly learn new technologies and apply them effectively in ambiguous problem spaces.
- Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
- Strong collaboration, communication, and mentorship abilities.
MINIMUM QUALIFICATIONS
- 9+ years of post-Bachelor’s machine learning experience; or a Master’s degree in a technical field + 8+ years of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
- 2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
- Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases
PREFERRED QUALIFICATIONS
- Advanced degree in a related field such as machine learning, computer vision, or mathematics
- Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures
- Experience with TensorFlow, PyTorch, or related deep learning frameworks
- Background in integrating recommendation models into production pipelines
- Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
- Experience contributing to AI publications
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
OUR BENEFITS
Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
COMPENSATION
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
Zone A (CA, WA, NYC):
The base salary range for this position is $276,000-$414,000 annually.
Zone B:
The base salary range for this position is $262,000-$393,000 annually.
Zone C:
The base salary range for this position is $235,000-$352,000 annually.
This position is eligible for equity in the form of RSUs.
INTRODUCTION
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
We’re looking for a Principal Machine Learning Engineer to join the Content ML team at Snap! We build large-scale recommender systems for all of Snap’s video content products.
ROLE AND RESPONSIBILITIES
- Lead the vision and roadmap for Snap’s large-scale recommendation systems, elevating content discovery and personalization across Spotlight, Discover, and Friend Stories.
- Technically lead a group of talented engineers from Content ML and Platform teams to operate and scale the existing recommender system.
- Work with cross-team ML, Infra, and Research partners to design the next-gen recommender system and incorporate SOTA industry research in recommendation systems, foundation models, multimodal signal understanding, deep user understanding, and related areas. We actively participate in and publish at top-tier conferences.
- Partner with engineers, product managers, research scientists, data science, and leadership to align on ML strategy and ensure technical investments support long-term company priorities.
- Advance the ML tech stack for recommendations, improving scalability, efficiency, reliability, and overall system performance.
- Stay up to date on emerging trends and advancements in the RecSys landscape and proactively identify opportunities to leverage these developments to further enhance Snap’s content capabilities.
- Advocate for and implement best practices in availability, scalability, experimentation rigor, operational excellence, and cost management.
KNOWLEDGE, SKILLS & ABILITIES
- Deep understanding of RecSys architectures and experience applying them to real-world production systems.
- Strong foundation in machine learning, deep learning, and large-scale recommendation/ranking systems.
- Experience leading teams or roadmaps focused on recommendations and/or personalization.
- Ability to design, train, deploy, and optimize state-of-the-art machine learning models for performance, reliability, and scale.
- Excellent programming and software engineering skills, with an emphasis on clean design and production-readiness.
- Ability to quickly learn new technologies and apply them effectively in ambiguous problem spaces.
- Skilled at solving complex technical challenges, influencing architecture decisions, and driving execution across multi-stakeholder environments.
- Strong collaboration, communication, and mentorship abilities.
MINIMUM QUALIFICATIONS
- 9+ years of post-Bachelor’s machine learning experience; or a Master’s degree in a technical field + 8+ years of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
- 2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
- Experience developing and shipping performant and scalable machine learning models for recommendation or ranking use cases
PREFERRED QUALIFICATIONS
- Advanced degree in a related field such as machine learning, computer vision, or mathematics
- Experience with large-scale recommendation/ranking systems, multimodal modeling, or retrieval architectures
- Experience with TensorFlow, PyTorch, or related deep learning frameworks
- Background in integrating recommendation models into production pipelines
- Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
- Experience contributing to AI publications
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
OUR BENEFITS
Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
COMPENSATION
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
Zone A (CA, WA, NYC):
The base salary range for this position is $276,000-$414,000 annually.
Zone B:
The base salary range for this position is $262,000-$393,000 annually.
Zone C:
The base salary range for this position is $235,000-$352,000 annually.
This position is eligible for equity in the form of RSUs.
See All 67 Machine Learning Engineer Jobs in Los Angeles
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Find JobsMachine Learning Engineer Job Market in Los Angeles
Who's Hiring
- SentiLink7
- Whatnot6
- Riot Games6
- TikTok5
- Snap4
Top Industries Hiring
- Technology & Software26
- Manufacturing7
- Retail6
- Media & Entertainment6
- Investment & Asset Management4
Machine Learning Engineer Jobs in Los Angeles: Frequently Asked Questions
How do I get a machine learning engineer job in Los Angeles?
Target the sectors that hire most heavily in Los Angeles: entertainment and media technology along the Westside, aerospace and defense firms in El Segundo and the South Bay, and health tech companies around the UCLA and USC medical corridors. Candidates who combine strong Python and deep learning skills with domain knowledge in one of those sectors consistently stand out in this market. Building a portfolio of applied projects relevant to those industries gives you a concrete edge.
Which companies hire machine learning engineers in Los Angeles?
Employers hiring machine learning engineers in Los Angeles right now include SentiLink, Whatnot, and Riot Games, based on current listings on Migrate Mate as of June 2026. Los Angeles attracts a broad mix of large media and entertainment conglomerates, aerospace contractors, and venture-backed startups, giving candidates options at every stage of company growth.
Are there remote machine learning engineer jobs in Los Angeles?
Yes, and machine learning engineering is among the more remote-friendly engineering disciplines since the core work revolves around code, data pipelines, and model training rather than physical infrastructure. About 55% of machine learning engineer openings tied to Los Angeles are remote or hybrid as of June 2026, reflecting how normalized flexible arrangements have become in local tech and media companies. Research and modeling work tends to be the most portable, while roles tied to on-site data centers or hardware labs remain in-office.
How can I get a machine learning engineer job in Los Angeles with little or no experience?
The most realistic entry path in Los Angeles is targeting junior data scientist or ML engineer roles at mid-size startups in Culver City, Santa Monica, and the broader Westside, where teams are small enough to give early-career candidates hands-on model work quickly. Many local entertainment tech and ad tech companies hire associates who can demonstrate project work in recommendation systems or computer vision. Internship programs at larger aerospace firms in El Segundo are another door worth pursuing, especially for candidates with a strong academic background in statistics or computer science.
Which industries hire the most machine learning engineers in Los Angeles?
Most machine learning engineer openings in Los Angeles sit in Technology & Software, Manufacturing, and Retail, per current listings on Migrate Mate as of June 2026. Los Angeles's unusual industry mix, anchored by one of the world's largest entertainment ecosystems alongside a major aerospace and defense presence and a growing health tech cluster, sustains demand for machine learning talent well beyond what you'd find in a typical tech hub.
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See All 67 Machine Learning Engineer Jobs in Los Angeles
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