软件工程师 - AI 会员系统

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

As Netflix continues to grow, so do the opportunities to enhance our personalization systems and algorithms. We're looking for a passionate and talented Software Engineer for Machine Learning to join our Al for Member Systems team. In this role, you will apply your expertise in software engineering to design, develop, and scale solutions for the machine learning algorithms that power the Netflix experience. You will work closely with our machine learning researchers, product managers, and other engineers to come up with new systems, improve existing ones, and enable offline experiments and A/B tests. For more details about software engineering for personalization at Netflix, see these links:

- [Consolidating ML models](https://netflixtechblog.medium.com/lessons-learnt-from-consolidating-ml-models-in-a-large-scale-recommendation-system-870c5ea5eb4a)

- [InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models](https://dl.acm.org/doi/10.1145/3604915.3608778)

- [Evidence Personalization](https://netflixtechblog.com/artwork-personalization-c589f074ad76)

- [Page Simulation for Better Offline Metrics at Netflix](https://netflixtechblog.com/page-simulator-fa02069fb269)

- [RecSysOps](https://netflixtechblog.medium.com/recsysops-best-practices-for-operating-a-large-scale-recommender-system-95bbe195a841)

As a software engineer in the team, you will contribute to the next generation of algorithms used to generate the Netflix experience by driving the vision, requirements, design, implementation, testing, and ownership of software components essential for our algorithmic innovation. You will collaborate with our applied researchers and data scientists to implement scalable, flexible, production-ready solutions for our algorithms. You will also guide the team towards better software engineering practices and systems by identifying areas for improvement and mentorship. You will collaborate with other engineers to create solutions that are used beyond our team. To excel in this role, you should have a robust software engineering background, a keen sense of software engineering principles and design, a proven experience with large-scale applications involving machine learning, a love of learning, possess strong communication skills, and the ability to work well in large cross-functional teams.

## **What we are looking for:**

- A degree in Computer Science or a related field

- 4+ years of full time software engineering experience with a bachelor’s degree; or 2+ years of experience with a graduate degree

- Excellent software design and development skills in Python along with Scala, Java, C++, or C#

- Solid understanding of various software engineering best practices and their appropriate application

- Experience building web-scale parallel and distributed computing systems

- Experience with large-scale data frameworks such as Spark or Flink

- Excellent collaboration skills

- Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems

## **Preferred, but not required:**

- Experience building or enhancing personalization systems, machine learning platforms, search engines, or similar large-scale machine learning applications.

- Experience building machine learning models or LLMs

- Experience scaling and optimizing the training and serving of machine learning models

- Experience with machine learning libraries TensorFlow, PyTorch, JAX or Keras

- Experience with cloud computing platforms like AWS

- Background in math, statistics, or numerical computation

- Significant contributions to open-source projects

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 $466,000.00 - $750,000.00. This compensation range will vary based on location.

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](https://jobs.netflix.com/work-life-philosophy).

Netflix is a unique culture and environment. Learn more [here](https://jobs.netflix.com/culture).

[Inclusion](https://about.netflix.com/en/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.