Machine Learning Engineer, Recommendations

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Udemy is a global company headquartered in San Francisco with additional U.S. offices in Denver and Austin and international hubs in Australia India Ireland Mexico and Türkiye. This is an in-office position requiring three days a week in the office (Tuesday Wednesday Thursday) and flexibility on Mondays and Fridays.

About this role

Udemy is looking for a machine learning engineer to join our Recommendations Team. Udemys personalized recommendations system is composed of batch (e.g. feature and machine learning pipelines) streaming (i.e. feature computation in real-time) and online (i.e. microservices to serve personalized recommendations) components. The team is responsible for all these components as well as the underlying machine learning algorithms and evaluation methodologies.

As a member of a cross-functional agile team comprising engineers and data scientists you will be responsible for designing building and integrating scalable systems. These systems will focus on enhancing recommendation quality and personalizing the learner experience with minimal latency. Your work will span a broad technology stack encompassing both data-related technologies and backend development.

Are you passionate about learning willing to take technical challenges care about making an impact and looking for a diverse collaborative and fun environment that also values

quality If so come help us improve lives through learning at Udemy!

Work authorization: Candidates must be legally authorized to work in the United States for any employer now and in the future without the need for employer-sponsored work authorization. This role is not eligible for current or future visa sponsorship or transfer (e.g. H-1B H-1B transfer O-1 TN E-3). Individuals working on F-1 OPT/STEM OPT who would require sponsorship to continue working in the U.S. after their OPT period are not eligible for this role.

About your skills

• Machine learning at scale: You have a strong knowledge of machine learning statistics and information retrieval coupled with practical real-world experience with implementing ML algorithms at scale.
• Problem Solving Mindset: You can solve problems and implement solutions across a wide range of technologies and within complex systems. You also have a growth mindset enabling you to learn new technologies even if they are outside your current expertise.

Execution: You are able perform tasks independently with minimal supervision and are comfortable navigating ambiguous technical tasks with some help from technical leads.

• Collaboration: You work effectively in cross-functional teams communicate clearly with non-technical stakeholders and are thoughtful while making tradeoffs.

What youll be doing

• Design develop test and deploy scalable recommendation and personalization systems platforms and tools.
• Develop high-performance ML models for real-time applications.
• Design and analyze experiments and monitor the performance of personalized recommendations.
• Translate data science prototypes into scalable production implementations.
• Partner with data scientists and engineers to troubleshoot and optimize complex data workflows.
• Collaborate with data scientists engineers and product managers to identify opportunities to improve our learner experience through personalization.

What youll have

• About 1-3 years building and supporting ML features at scale in production.
• Comfortable with computer science fundamentals (OOP data structures algorithms) and writing clean maintainable code.
• Practical applied knowledge of statistics and machine learning; exposure to recommender systems/personalization or NLP is a plus.
• Proficiency in Python; familiarity with Java or Kotlin is a plus. Comfortable picking up new languages/paradigms as needed.
• Experience with at least one of scikitlearn PyTorch or TensorFlow (no need to have all three).
• Comfortable with SQL and batch data processing; experience with Spark/Hive (or similar) is a plus.

Why work here

Youll grow here.
Learning is part of the job. Youll get full access to Udemy courses a monthly UDay to invest in yourself and a budget to spend on whatever helps you improve. Many people are diving into AI lately but what you focus on is up to you.

AI is real here.
We use it in the way we learn and the way we work. Youll have the space and tools to experiment apply and get better at using AI in practical ways.

Youll own your work.
We trust people to lead make decisions and follow through. You dont need to wait for permission or layers of approval to have an impact.

Youll build with others.
We collaborate openly and shape ideas together. Everyone has a voice and good thinking is welcomed from any direction.

Youll see your impact.
What you build helps people grow their skills change their careers or find a path forward. Youve got the experience why not use it to help others gain theirs

Bring your curiosity. Well bring the platform and the support. Lets LEARNtogether.

Our Benefits Start with U

Our benefits start with you and were built to provide you and your family with the protection and care you need making it easy to access the right coverage when you need it most. Benefits vary by region and we encourage applicants to review our Australia Benefits India Benefits Ireland Benefits Mexico BenefitsTurkiye Benefits & US Benefitspages to get an understanding of some of the benefits we offer. For details on region-specific benefits please refer to the information provided during the hiring process.

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