Applied Machine Learning Backend Engineer (L5) - Monitoring & Alerting
Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The Observability Team provides a platform and suite of products that enable Netflix engineers to monitor service behavior in real time, detect system health anomalies, and troubleshoot issues. This role is part of the Monitoring and Alerting team, a crucial part of our Observability engineering group.
As part of the team, you will:
Work across a suite of observability products including System Health Experience, Alert configuration and management tools and Issue Management Experience.
Define and implement a forward-looking strategy for Netflix's AI Ops platform, focusing on the integration of Machine Learning algorithms and cutting-edge Generative AI techniques to enhance application resilience in conjunction with observability platforms.
Build Systems that integrate internal Observability data with LLMs for more effective guidance when diagnosing issues.
Contribute to a platform that processes billions of data points in real time every minute
Provide mentorship to early career engineers on the team, fostering their growth and development.
About You:
6+ years of experience in high-scale, modern tech-driven companies.
You consider yourself an Applied Machine Learning engineer and have experience in both developing backend and applying Machine Learning algorithms at scale for a good part of your career. You act like an owner and have expertise in building and maintaining backend services
You are proficient in designing, building, and operating algorithms or leveraging APIs for Monitoring and Alerting applications. You are familiar with the latest techniques and applications of Generative AI.
You are proficient in distributed computing frameworks that enable efficient handling, analysis, and processing of large datasets, such as Apache Spark for fast, in-memory data processing, and Apache Kafka for real-time data streaming.
You have built, maintained, evolved, and/or sunset a variety of APIs. You can confidently describe the API’s schema, purpose, response types, and up/down-stream services.
You are proficient in working with Java (or JVM language) and Python.
You are knowledgeable about and are willing to own all areas of the software lifecycle: design, development, test, deploy, operate, and support.
You possess exceptional communication and collaboration skills, effectively engaging with a diverse, cross-functional team of stunning colleagues. Capable of working independently, yet excel in a dynamic team environment.
Have a product mindset that is deeply empathetic to customer needs, strategic in orientation, and metrics and outcomes-driven.
Nice To Have
You have used or built observability products involving logs, metrics, and traces.
Familiar with ML algorithms for detection and classification of system faults, such as Real-time anomaly detection, Outlier detection, time series analysis and forecasting, etc.
About Netflix
Our culture is unique, and we live by our values, so it’s worth learning more about Netflix culture.
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 $100,000 - $720,000.
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 detail about our Benefits 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.
Job is open for no less than 7 days and will be removed when the position is filled.
About the job
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Applied Machine Learning Backend Engineer (L5) - Monitoring & Alerting
Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.
The Observability Team provides a platform and suite of products that enable Netflix engineers to monitor service behavior in real time, detect system health anomalies, and troubleshoot issues. This role is part of the Monitoring and Alerting team, a crucial part of our Observability engineering group.
As part of the team, you will:
Work across a suite of observability products including System Health Experience, Alert configuration and management tools and Issue Management Experience.
Define and implement a forward-looking strategy for Netflix's AI Ops platform, focusing on the integration of Machine Learning algorithms and cutting-edge Generative AI techniques to enhance application resilience in conjunction with observability platforms.
Build Systems that integrate internal Observability data with LLMs for more effective guidance when diagnosing issues.
Contribute to a platform that processes billions of data points in real time every minute
Provide mentorship to early career engineers on the team, fostering their growth and development.
About You:
6+ years of experience in high-scale, modern tech-driven companies.
You consider yourself an Applied Machine Learning engineer and have experience in both developing backend and applying Machine Learning algorithms at scale for a good part of your career. You act like an owner and have expertise in building and maintaining backend services
You are proficient in designing, building, and operating algorithms or leveraging APIs for Monitoring and Alerting applications. You are familiar with the latest techniques and applications of Generative AI.
You are proficient in distributed computing frameworks that enable efficient handling, analysis, and processing of large datasets, such as Apache Spark for fast, in-memory data processing, and Apache Kafka for real-time data streaming.
You have built, maintained, evolved, and/or sunset a variety of APIs. You can confidently describe the API’s schema, purpose, response types, and up/down-stream services.
You are proficient in working with Java (or JVM language) and Python.
You are knowledgeable about and are willing to own all areas of the software lifecycle: design, development, test, deploy, operate, and support.
You possess exceptional communication and collaboration skills, effectively engaging with a diverse, cross-functional team of stunning colleagues. Capable of working independently, yet excel in a dynamic team environment.
Have a product mindset that is deeply empathetic to customer needs, strategic in orientation, and metrics and outcomes-driven.
Nice To Have
You have used or built observability products involving logs, metrics, and traces.
Familiar with ML algorithms for detection and classification of system faults, such as Real-time anomaly detection, Outlier detection, time series analysis and forecasting, etc.
About Netflix
Our culture is unique, and we live by our values, so it’s worth learning more about Netflix culture.
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 $100,000 - $720,000.
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 detail about our Benefits 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.
Job is open for no less than 7 days and will be removed when the position is filled.