Welcome to Warner Bros. Discovery… the stuff dreams are made of.
Who We Are…
When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next…
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
Senior Manager, Machine Learning Engineering (Growth & ML), Hyderabad
About Warner Bros. Discovery
Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses.
For more information, please visit www.wbd.com.
Meet Our Team
Warner Bros. Discovery (WBD) is home to the world’s most iconic entertainment, news, and sports brands — HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, Food Network, and many more. Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team in Hyderabad builds the foundational AI/ML intelligence that powers identity, audience, advertising, and personalization across every WBD brand. We turn first-party signals from hundreds of millions of viewers into production ML systems that expand addressable audiences, sharpen targeting and measurement, forecast demand, and personalize content discovery — directly driving advertising yield, marketing efficiency, engagement, and retention.
At WBD, MLEs do rigorous data science and own the engineering that brings models to life: production ML data pipelines, model training and optimization, and the ML infrastructure — feature stores, training and serving pipelines, and MLOps — that makes our work reliable, repeatable, and scalable. We build primarily on Databricks, with strong working knowledge of Snowflake and AWS, and we are an early, enthusiastic adopter of agentic AI development workflows.
About the Role
This is the most critical hire for WBD’s Hyderabad ML Engineering build-out. As Senior ML Engineering Manager, you will establish, lead, and grow the Hyderabad ML Engineering center of excellence — a team of seven individual contributors spanning identity intelligence, audience intelligence, content affinity modeling, forecasting, and ML platform engineering. You will be the single accountable leader for the team’s technical execution, people development, and cross-functional delivery in India, operating as a true extension of the Director of Engineering. All of the Hyderabad ML/DS individual contributors report to you, and you report into the Director.
This role demands an exceptional blend of technical depth (you must credibly engage in Staff-level ML architecture discussions), people leadership (you will manage a diverse IC ladder from MLE 2 to Staff), and organizational influence (you will represent Hyderabad across WBD’s global data, product, and advertising organizations). You are not just a manager — you are a builder, a technical partner, and a culture carrier.
Roles & Responsibilities:
Team Leadership & People Development
Directly manage 7 ICs (2× MLE 2, 3× Senior MLE, 1× Staff MLE, 1× Staff DS); own their performance, growth, and career development.
Establish a high-performance engineering culture: technical excellence, ownership, psychological safety, rigorous experimentation, and continuous learning.
Define clear role expectations, growth paths, and promotion criteria aligned with WBD’s global ML engineering job family; conduct regular 1:1s, performance reviews, and career conversations, addressing performance gaps proactively.
Lead hiring for the Hyderabad team: define the hiring bar, design interview processes, attract top ML talent, and build a strong, diverse local pipeline.
Foster an inclusive, collaborative environment that bridges India and US time zones effectively.
Technical Leadership & Oversight
Maintain sufficient technical depth to review ML architecture proposals, challenge design decisions, and unblock technical escalations across all workstreams.
Partner with the Staff MLE to set and enforce technical standards: MLOps practices, code quality, model-evaluation rigor, and documentation.
Own the technical roadmap for the team’s ML systems — identity intelligence, audience intelligence, content affinity, forecasting — in alignment with global ML strategy.
Drive adoption of the team’s core stack: Databricks (primary), AWS SageMaker, Snowflake, MLflow, and agentic AI tooling (Cursor, Copilot, Amazon Q, Databricks Genie, Snowflake Cortex, MCP).
Ensure production ML systems are reliable, monitored, cost-efficient, and continuously improved; own the team’s on-call and incident-response posture.
Program Execution & Delivery
Own end-to-end delivery accountability for Hyderabad’s ML projects: scope, milestones, dependencies, risks, and stakeholder communication.
Run effective agile processes adapted to ML realities (research uncertainty, data dependencies, experiment iteration), with D90 planning rhythms and quarterly OKR alignment.
Proactively identify and resolve cross-team dependencies with Data Engineering, Product, Ad Sales, and Legal/Privacy.
Maintain a clear view of capacity, prioritization trade-offs, and commitments; communicate status and risks transparently to the Director.
Key ML Workstream Ownership
Identity Intelligence: oversee delivery of the probabilistic ID spine — resolving unauthenticated signals (device IDs, 1P cookies) to households/persons with calibrated confidence across all WBD brands.
Audience Intelligence: oversee ML Promo Optimizer, STAT v2 (single-title affinity retrieval), lookalike modeling (LAL 2.0+ in Snowflake DCR), and segmentation that power advertising and marketing activation.
Content Affinity & Personalization: oversee genre-preference and content-affinity models and engagement-based personalization signals feeding HBO Max and CNN surfaces.
Forecasting: oversee ML-based audience, engagement, and yield/revenue forecasting supporting Finance, Content, and Marketing planning.
MLOps Platform: ensure the team’s feature store, training/serving pipelines, model registry, and monitoring are production-grade, well-documented, and consistently adopted.
Cross-functional & Organizational Leadership
Serve as the primary point of contact for the Hyderabad ML team across Product, Marketing, Ad Sales, Data Engineering, Legal/Privacy, and Finance.
Build strong relationships with US-based ML leadership, Data Science, and Platform Engineering counterparts so Hyderabad is a fully integrated — not siloed — part of the global ML organization.
Partner with the Director on long-range team strategy, capability planning, and organizational design; represent WBD ML externally where appropriate (talent branding, university partnerships).
Ensure ML systems meet privacy, governance, and compliance requirements.
What You’ll Bring
12+ years of total experience in ML, data science, or ML engineering, including 3–5+ years in engineering management.
Demonstrated success leading and growing teams of ~6–12 ML engineers and/or data scientists, including a multi-level IC ladder (junior through Staff).
Strong technical foundation in ML: you can read and critique model-architecture proposals, review ML code, and engage credibly in Staff-level discussions — you have personally built and shipped production ML.
Hands-on (current or recent) experience with the ML stack: Python, Databricks/Spark, MLflow, cloud ML (AWS SageMaker preferred), and SQL/Snowflake.
Proven track record delivering complex, multi-month ML projects in production at scale.
Experience in a matrixed, global organization with cross-timezone collaboration.
Excellent communication: translating technical complexity for executive and non-technical audiences, and business context for engineers.
Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field.
Preferred
ML leadership in streaming, media, ad-tech, or consumer internet — particularly audience modeling, identity resolution, personalization, or recommendations.
Familiarity with WBD’s ecosystem: Databricks, Snowflake, AWS, FreeWheel/GAM, or equivalent ad-tech activation stacks.
Experience managing teams across India and US time zones, and building ML teams from early stages (hiring bar, onboarding playbooks, culture).
Familiarity with Databricks Genie, Snowflake Cortex, MCP, and modern AI-assisted development workflows.
Experience with Data Clean Rooms and privacy-preserving ML.
What We Offer:
How We Get Things Done…
This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.
Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.
If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.
