Machine Learning Engineer, Entry
Role details
Job location
Tech stack
Job description
As a member of the Applied Machine Learning Group, you'll help build a world-class streaming experience within the team. Your mission is to get the user watching. You own the "onboarding" and "re-entry" experience, including high-commitment surfaces like Your Next Watch (YNW), Jump Back In (JBI), and While You Were Away (WYWA). You'll put customers first by using MLFlow for experiment tracking, Qdrant for retrieval, and Post-training RL to ensure that the content we surface at the start of a session is what the user is most likely to commit to. You will be in charge of implementing the components that solve the "Cold Start" problem for new users and provide seamless re-entry for returning ones. You'll work in an IC2 (Mid-level) role to ensure these surfaces, which optimize for Start Rate under uncertainty, identify if a user stays or leaves within the first 30 seconds of app launch., * Independent Delivery: Own the implementation of features for JBI (Jump Back In) and YNW (Your Next Watch).
- Retrieval Optimization: Use Qdrant to find high-relevance candidates for re-entry carousels based on session history and global trends.
- Experiment Lifecycle: Use MLFlow to manage, track, and deploy experiments, ensuring a high bar for reproducibility.
- Model Training: Develop and serve models in GCP using TensorFlow/PyTorch, incorporating Post-training RL for reward-based optimization.
- Collaborative Quality: Participate in design reviews to ensure your components share the same high-reliability standards as the rest of the pod.
- Solving Cold Start: Build the logic that makes the app feel personalized even for users we know very little about.
- High-Commitment Accuracy: Optimize for the "Play" button-the ultimate signal of user commitment.
Requirements
- 3+ years in MLE.
- Experience with GCP and MLFlow.
- Proficiency in TensorFlow/PyTorch.
- Knowledge with Vector DBs.
- Proven ability to implement features that solve the "Cold Start" problem for new users.
- Experience managing, tracking, and deploying experiments to ensure a high bar for reproducibility.
Bonus Skills
- Background in multi-stage ranking or "Cold Start" problems.
- Experience with retrieval optimization and re-entry carousels.
- Knowledge with Post-training RL for reward-based optimization.
Benefits & conditions
Hiring Salary Range: $124,000.00 - 186,000.00.
The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement. This position is bonus eligible., * Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits
- Generous paid time off.
- An exciting and fulfilling opportunity to be part of one of Paramount's most dynamic teams.
- Opportunities for both on-site and virtual engagement events.
- Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.
- Explore life at Paramount: https://www.paramount.com/careers/life-at-paramount
Paramount is an equal opportunity employer (EOE) including disability/vet.
At Paramount, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. Paramount is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.