Top Tech Jobs & Startup Jobs

Design, build, and evaluate large-scale ML-driven bidding algorithms for ad optimization (clicks, conversions, CPA, ROAS). Develop online/offline evaluation frameworks, inform auction/pricing design, partner with product, and communicate results to technical and non-technical stakeholders.

Build and scale robust production data pipelines and automate complex game-related datasets, ensure high data quality, design schemas and data models, collaborate with logging infrastructure and analytics stakeholders to enable analysis across Netflix's games library.

Lead a team of ML engineers and researchers to build next-generation content personalization and recommendation algorithms across movies, games, and live events. Define vision and strategy, drive projects end-to-end from research to production and A/B tests, collaborate cross-functionally, hire and mentor, and improve systems using transfer learning, ranking, bandits, and deep learning.

Lead end-to-end analytics and machine learning efforts for Netflix Ads: build and deploy predictive models and optimization algorithms, perform data exploration, produce datasets and tools, define and validate success metrics, collaborate cross-functionally, and communicate insights to influence product and business decisions.

Lead design and implementation of credit and collections policies across B2B revenue streams, implement automation and 3rd-party tools, manage customer credit processing and ERP records, oversee AR and Collections workflows, minimize DSO during deal negotiations, track credit and collections metrics, support monthly close, and drive process improvements while leading a geographically dispersed team.

Design cinematic, content-forward product experiences across TV, mobile, and web. Create high-fidelity prototypes, visual systems, and brand assets; collaborate with motion, audio, product, engineering, and research to ship scalable, story-driven UX that meets business goals.

Design, build, and operate resilient, high-scale, low-latency distributed microservices for production planning or media workflows. Implement gRPC/GraphQL/REST APIs, drive architectural decisions, ensure observability, performance, and fault tolerance, collaborate with cross-functional partners, participate in on-call rotation, and lead incident reviews. Knowledge of media encoding pipelines and AI-assisted tools is a plus.

Design and implement efficiency improvements for large-scale deep neural networks and LLM training/serving. Develop optimizations (quantization, pruning, distillation, efficient fine-tuning), work on ML hardware/software accelerator integration, and build scalable training and serving infrastructure in collaboration with scientists and cross-functional teams.

Provide high-volume administrative support to three to four Directors across Live and Merchandising: manage complex calendars and meetings across time zones, coordinate domestic and international travel and expenses, prepare agendas and materials, plan events and offsites, coordinate live operations logistics, maintain team communications and distribution lists, liaise with workplace team, and support team projects and communications.

Build scalable, privacy-focused data frameworks and ETL pipelines using big-data technologies (Spark, Presto, Flink, Kafka, Hive). Ensure appropriate handling of personal data, support privacy and legal needs, partner cross-functionally, and lead system design while mentoring teammates.