Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
  • The site is refreshed daily to remove out-of-date content.
  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.

Job Information

Netflix Research Scientist/Engineer L5 - Algorithms Engineering in Los Gatos, California

Netflix is one of the world's leading entertainment services with 270 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.

As Netflix continues to grow, we are venturing into exciting new frontiers of personalization to help our members find the content they’ll most enjoy. To do this, we have to understand which titles, and what experiences in the product, produce the most joy for each member.

We are looking for exceptional individuals to work full time with us as research scientists. This includes researching and applying cutting edge machine learning techniques to understand how members experience titles, and how that changes their long-term assessment of their satisfaction with the Netflix service. In this role, you will conduct applied research by conceptualizing, designing, implementing and validating the next generation of personalization algorithms using techniques such as causal inference, machine learning, reinforcement learning (specifically rewards models), and econometrics. You will be responsible for operating, as well as innovating on, these algorithms in production, and validating through running offline experiments, and building online A/B tests to run in production systems. You will partner with people from many disciplines, including behavioral scientists, machine learning researchers, and application engineers.

To be successful in this role, you need a strong machine learning background, solid software development skills, a love of learning, a passion for solving end-user problems and to collaborate well in multi-disciplinary teams. You will need to exhibit strong communication and leadership skills, an ability to set priorities, and an execution focus in a dynamic environment.

What we are looking for:

  • A burning desire to solve real world problems at scale by applying Machine Learning

  • PhD or Masters in Computer Science, Statistics, or any of the related fields

  • 5+ years of research experience with a track record of delivering quality results

  • Experience in end-to-end ML application development

  • Expertise in machine learning spanning supervised and unsupervised learning methods

  • Excellent software engineering skills in multi-language settings with Scala, Java, and Python

  • Experience with Spark, TensorFlow, Keras, or PyTorch

  • Exceptional problem solving skills

  • Strong mathematical skills with knowledge of statistical methods

  • Great interpersonal skills

  • Strong written and verbal communication skills

Preferred, but not required:

  • Experience using Reward models, LLM Alignment models of RLHF in real world applications

  • Experience in Personalization, Recommendations, Deep Learning, Bandits, CausalML, Industrial scale ML systems, etc

  • Experience as a technical leader

  • Experience working with cross functional teams

  • Experience with cloud computing platforms and large web-scale distributed systems

  • Experience in applied research in industrial settings

  • Open source contributions

  • Research publications at peer reviewed journals and conferences on relevant topics

Links:

  • Netflix Research site (https://research.netflix.com/)

  • Our culture

  • Our long term business view (https://ir.netflix.net/ir-overview/long-term-view/default.aspx)

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

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

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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.

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