Senior Manager, Machine Learning Engineering (Data & Audience Platform), Hyderabad

Warner Bros. Discovery; Hyderabad; On-site; INR 2,500,000 - 4,500,000; Full time

Benefits offered by this job

Fast track growth opportunities

Equal opportunity employer

Great workplace

Job summary

Warner Bros. Discovery seeks a Senior ML Engineering Manager in Hyderabad to lead the ML Engineering team. You will be responsible for technical execution, people development, and driving a culture of excellence among a diverse group of ML engineers.

Your role entails overseeing various ML workstreams, from identity and audience intelligence to forecasting challenges, while ensuring successful project delivery across global teams. You'll champion innovation through agentic AI and maintain collaborative cross-functional relationships.

Qualifications

• 12+ years of experience in ML, data science, or ML engineering; 3-5+ years in engineering management.
• Strong technical foundation in ML with hands-on experience in the ML stack.
• Proven track record delivering complex ML projects in production.

Responsibilities

• Lead and grow the ML Engineering team in Hyderabad, ensuring technical execution and people development.
• Own end-to-end delivery for ML projects, managing scope, milestones, and risks.
• Establish a high-performance culture and hiring processes for the team.

Skills

ML architecture expertise

People leadership

Cross-functional collaboration

Python

Cloud ML (AWS SageMaker)

SQL/Snowflake

Education

Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related quantitative field

Tools

Databricks

MLflow

AWS

Job description

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 to 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.

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.

Agentic AI & Innovation Culture

• Champion agentic AI development: establish norms for using Cursor, GitHub Copilot, Amazon Q, and MCP‑based tooling to accelerate ML velocity, with measurable improvements in quality and lifecycle efficiency.
• Drive strategic adoption of Databricks Genie (governed, self‑service NL interfaces over Unity Catalog) and Snowflake Cortex (Copilot/Analyst, Cortex Search, and selective Fine‑Tuning) so ML outputs are accessible to non‑technical stakeholders.
• Create space for innovation: structured prototyping time, internal tech talks, and contribution to WBD’s broader ML community of practice; bring relevant external insights into the roadmap.

What You’ll Bring

Required

• 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

• A Great Place to work
• Equal opportunity employer
• Fast track growth opportunities

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.