This is a collaborator role rather than a research or dedicated-MLE position; fluency and partnership matter more than authoring the models. * Public / external-facing API engineering - experience ...
This is a collaborator role rather than a research or dedicated-MLE position; fluency and partnership matter more than authoring the models. * Public / external-facing API engineering - experience ...
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Ways to Stand Out from the Crowd: * Hands-on ML platform depth (MLE experience or strong ...
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Ways to Stand Out from the Crowd: * Hands-on ML platform depth (MLE experience or strong ...
Required : • 12+ years of software engineering experience delivering production web systems. • ... Preferred : • Hands-on ML platform depth (MLE experience or strong familiarity with DL frameworks ...
Required : • 12+ years of software engineering experience delivering production web systems. • ... Preferred : • Hands-on ML platform depth (MLE experience or strong familiarity with DL frameworks ...
Senior Full-Stack Lead Engineer
Santa Clara, CA · On-site
$224 - $356.50/hr
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Hands-on ML platform depth (MLE experience or strong familiarity with DL frameworks such as PyTorch ...
Senior Full-Stack Lead Engineer
Santa Clara, CA · On-site
$224 - $356.50/hr
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Hands-on ML platform depth (MLE experience or strong familiarity with DL frameworks such as PyTorch ...
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Ways to Stand Out from the Crowd: * Hands-on ML platform depth (MLE experience or strong ...
We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX ... Ways to Stand Out from the Crowd: * Hands-on ML platform depth (MLE experience or strong ...
Senior Full-Stack Lead Engineer
Santa Clara, CA · On-site
$224 - $356.50/hr
We're looking for a Senior Full‑Stack Software Engineer to join the AI Hub team within the DGX ... Hands‑on ML platform depth (MLE experience or strong familiarity with DL frameworks such as ...
Senior Full-Stack Lead Engineer
Santa Clara, CA · On-site
$224 - $356.50/hr
We're looking for a Senior Full‑Stack Software Engineer to join the AI Hub team within the DGX ... Hands‑on ML platform depth (MLE experience or strong familiarity with DL frameworks such as ...
Senior Machine Learning Engineer
San Francisco, CA · On-site
$144K - $190K/yr
Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... engineering with a focus on model optimization, distillation, and deployment. • Hands-on ...
Senior Machine Learning Engineer
San Francisco, CA · On-site
$144K - $190K/yr
Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... engineering with a focus on model optimization, distillation, and deployment. • Hands-on ...
Senior Machine Learning Engineer
San Francisco, CA · On-site
$144K - $190K/yr
Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... engineering with a focus on model optimization, distillation, and deployment. • Hands-on ...
Senior Machine Learning Engineer
San Francisco, CA · On-site
$144K - $190K/yr
Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... engineering with a focus on model optimization, distillation, and deployment. • Hands-on ...
Backend Software Engineer Graduate (TikTok-PGC-Digital Content Center) - 2027 Start
San Jose, CA · On-site
$128K - $256K/yr
... MLE) concepts and practices, including model training, deployment, and evaluation. - Open-source contributions, technical blog posts, or programming awards are a plus. - Go experience is a plus ...
Backend Software Engineer Graduate (TikTok-PGC-Digital Content Center) - 2027 Start
San Jose, CA · On-site
$128K - $256K/yr
... MLE) concepts and practices, including model training, deployment, and evaluation. - Open-source contributions, technical blog posts, or programming awards are a plus. - Go experience is a plus ...
Senior AI/ML Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Minimum of 5+ years of software engineering experience, with significant recent focus on AI/ML ... MLE experience: hands-on experience building, training, and serving at least one custom model in ...
Senior AI/ML Engineer
San Francisco, CA · On-site
$123K - $169K/yr
Minimum of 5+ years of software engineering experience, with significant recent focus on AI/ML ... MLE experience: hands-on experience building, training, and serving at least one custom model in ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
Engineering Manager, MLE
San Francisco, CA · On-site
$293K - $385K/yr
About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the ... Work closely with researchers, software engineers, and product managers to understand complex ...
Engineering Manager, MLE
San Francisco, CA · On-site
$293K - $385K/yr
About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the ... Work closely with researchers, software engineers, and product managers to understand complex ...
Senior Machine Learning Engineer, LLM Inference Optimization
Palo Alto, CA · On-site
$195K - $262K/yr
Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and ... A Senior MLE owns substantial model and endpoint optimization projects end to end. They are deeply ...
Senior Machine Learning Engineer, LLM Inference Optimization
Palo Alto, CA · On-site
$195K - $262K/yr
Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and ... A Senior MLE owns substantial model and endpoint optimization projects end to end. They are deeply ...
Founding Machine Learning Engineer
San Francisco, CA · On-site
$120 - $160/hr
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
New
Founding Machine Learning Engineer
San Francisco, CA · On-site
$120 - $160/hr
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
New
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
Experience recruiting for other technical areas outside of hardware, such as Machine Learning (MLE) or Software Engineering.
Experience recruiting for other technical areas outside of hardware, such as Machine Learning (MLE) or Software Engineering.
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
... software, and labor costs to get paid. Wholesail is building a financial network from the ground up ... The first MLE on this team gets to decide what we build with it. The problems are real and the ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
You will lead the strong team of MLE, SWE, and data engineers responsible for delivering efficient ... Develop sophisticated on-device and on-server software frameworks for context integration fast and ...
Senior Machine Learning Engineer, LLM Inference Optimization
Palo Alto, CA · On-site +1
$144K - $189K/yr
... engineering ... A Senior MLE owns substantial model and endpoint optimization projects end to end. They are deeply ...
Senior Machine Learning Engineer, LLM Inference Optimization
Palo Alto, CA · On-site +1
$144K - $189K/yr
... engineering ... A Senior MLE owns substantial model and endpoint optimization projects end to end. They are deeply ...
Software Engineer Mle information
What is the difference between Software Engineer Mle vs Data Scientist?
| Aspect | Software Engineer Mle | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's in CS or related, knowledge of ML frameworks | Bachelor's or higher in CS, statistics, or related |
| Work Environment | Develops ML models, integrates into software products | Analyzes data, builds predictive models, reports insights |
| Employer & Industry Usage | Tech companies, startups, AI-focused firms | Tech, finance, healthcare, research institutions |
While both roles involve machine learning, Software Engineer Mle focuses on integrating ML models into software applications, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and work environment.
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Full-time
Medical, Life, Retirement, PTO
Posted 10 days ago
Netflix rating
5.8
Based on 15 frontline employees who took The Breakroom Quiz
70th of 76 rated media
Job description
Our Team
The Ads Platform Engineering org builds advertising systems and integrations that power the delivery of ads using our world-class content delivery ecosystem. We use a number of Netflix investments and innovations to power our ads - a unique mix of client and server-side ad insertions, state-of-the-art content delivery systems, ad encoding recipes, content understanding and metadata, etc. We respect the viewing experience while driving great outcomes for advertisers. We also ensure advertiser brand safety during serving, and that members only see the most appropriate ads for them.
The Media Planning team is at the heart of designing and delivering state-of-the-art media planning solutions that power Netflix's advertising business. We develop innovative, in-house ad tech systems that enable advertisers and internal partners to plan, allocate, and optimize media investments across Netflix's platform. Our technology translates advertiser objectives into actionable media plans, ensuring seamless integration, automation, optimization, compliance, and management of media strategies at scale. We work closely with cross-functional teams to deliver capabilities that serve our advertisers, members, and Netflix's broader business goals.
Our team's core focus areas in media planning include:
• Building applications and APIs that support every stage of the media planning process, from initial plan creation and inventory allocation through to campaign activation and completion.
• Delivering transparency on media plan performance and providing users with actionable insights to optimize their strategies.
• Partnering closely with our applied-science colleagues to bring optimization, forecasting, and LLM/agentic capabilities into production as reliable, observable, and performant services.
• Building the shared services and data pipelines that keep those capabilities dependable and well-understood in production.
• Partnering with stakeholders across the Ads Platform (Engineering, Product, Data Science, and Design) to develop scalable, impactful media planning solutions that drive business value.
Our team is new and yet faced with the enormous ambitions of building highly performant advertising systems and delivering high impact to our business by monetizing our incredible slate of content. As one of the newest entrants in the Connected TV advertising space that's rapidly growing, we seek to build unique value propositions that help us differentiate from the competition and become a market leader in record time.
We are looking for highly motivated engineers working in the advertising space who are excited to join us on this journey.
Skills & experience we're seeking:
- Experience building modern backend and frontend applications on cloud / AWS using Java, Spring Boot, GraphQL or equivalent technologies.
- Experience with distributed systems and microservices, modern databases, queues, and workflow orchestration.
- Solid understanding of CI/CD pipelines and DevOps practices.
- Advertiser facing / demand-side experience: familiarity with key concepts including, but not limited to Media Planning, Audiences, Creatives, Measurement, Forecasting, Optimization, Ad Serving, Reporting, Billing, and Campaign or Order Management.
- Proven track record of championing AI adoption within a team, building standardized workflows that leverage generative AI.
- Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.
- Broad knowledge of ad tech and advertising landscape, programmatic advertising, and digital marketing trends.
- Excellent communication, negotiation, and relationship-building skills.
Strongly preferred (depth in any one of these areas is a significant plus):
- Applied ML / Gen AI engineering - hands-on experience applying AI, ML, or Gen AI to product problems, with the ability to read, reason about, and debug model and algorithm code - including comfort building and debugging the infrastructure around production agentic models: model deployment, real-time feature hydration, and integrating ML models into existing applications at scale. This is a collaborator role rather than a research or dedicated-MLE position; fluency and partnership matter more than authoring the models.
- Public / external-facing API engineering - experience designing and operating partner-facing APIs as a product: contract-first design, versioning and backward compatibility, idempotency, rate limiting and quota management, authentication, and developer experience (OpenAPI/Swagger, sandbox and dry-run environments)
- Media planning / ads domain depth - hands-on experience across the media-planning and pre-sales lifecycle, from RFPs through campaign activation, including agency and holding-company planning tools and programmatic guaranteed / deal-based buying workflows.
Nice to haves:
- Contributed to an ads industry technology standard (e.g., VAST, OpenRTB) or worked on an industry consortium effort, working group, etc.
- Familiarity with legal compliance and the changing landscape of ads regulations around the world.
- Experience working in the CTV space and knowledge of its unique constraints.
- Familiarity with recommendation systems, optimization, causal measurement, or experimentation frameworks.
- Exposure to big-data / ML tooling (e.g., Spark, Flink, feature/data pipelines).
Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $388,000.00 - $558,000.00.
Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.
Netflix is a unique culture and environment. Learn more here.
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
About Netflix
Sourced by ZipRecruiter
Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.
Industry
Arts, entertainment, and recreation
Company size
5,001 - 10,000 Employees
Headquarters location
Los Gatos, CA, US
Year founded
1997