Job Summary

We're building a unified data and AI/ML model development and training platform similar in ambition to those platforms at other media technology companies to accelerate our entire AI/ML lifecycle from data preparation and feature computation to experimentation, large-scale distributed training, evaluation, deployment, and governance & observability.

As Senior Manager, Data & AI Platform, you will lead the team responsible for integrating the data systems, compute orchestration, and AI/ML tooling and exposing these core platform services through high quality APIs and SDKs, which hide infrastructure complexity and maximize practitioner velocity across Dolby teams working on audio, video, personalization, content understanding, and generative AI. A major focus is creating horizontal, reusable components feature pipelines, embedding services, training/evaluation frameworks, SDKs, and model management APIs to simplify the end to end AI/ML lifecycle.

Your work will enable researchers and engineers to move rapidly and safely from early experimentation to production, with standardized workflows, governance, observability, repeatability and reproducibility, and developer productivity built in.

Key Responsibilities

- Set a multi year platform roadmap that integrates data pipelines, AI/ML workflows, and compute orchestration layers across cloud and on prem infrastructure ensuring seamless experience spanning dataset creation to model training, evaluation, and deployment.
- Build a unified platform that abstracts complex underlying engines (Spark, Ray, Kubernetes, Airflow/Flyte/Metaflow, etc.) to provide secure, governed, cohesive workflows.
- Deliver robust APIs, SDKs and developer friendly tools and interfaces (CLIs, GUIs,



dashboards, etc) to enable AI/ML researchers and engineers to build repeatable, modular, composable end to end workflows/pipelines from dataset selection and preparation through model training, evaluation, tuning, and deployment.
- Ensure that all stages of the AI/ML lifecycle dataset selection, feature engineering, training, evaluation, tuning and AI/ML artifact management can be orchestrated via consistent, versioned workflows with full lineage and reproducibility.
- Provide guardrails and governance around data and AI/ML models while enabling researchers to move from exploratory work to production-level pipelines with minimal friction by leveraging common evaluation frameworks and automated checks.
- Partner with platform engineering/MLOps and infrastructure to define observability stacks for metrics, drift indicators, performance regressions, training/inference health signals, production reliability (SLIs/SLOs), monitoring, and incident response.
- Hire, mentor, and develop architects and senior engineers across data infrastructure and developer experience.

What you need to succeed Desired Background
- BS in Computer Science, Mathematics, Engineering, or equivalent technical field. Master's highly preferred.
- Proven platform leadership delivering integrated Data and AI/ML platforms used at enterprise scale,



with deep experience integrating data processing, orchestration, and AI/ML frameworks and tools to deliver consistent, standardized workflows and pipelines.
- Robust API/SDK design experience enabling AI/ML researchers and engineers to build reliable, reusable, and scalable pipelines.
- Deep knowledge and extensive experience with GPU infrastructure, distributed systems, orchestration engines, AI/ML toolchains, query engines, pipeline technologies i.e., Ray, Spark, Metaflow / Flyte / Airflow / Argo / Kubeflow , Kubernetes.
- Deep expertise across the AI/ML ecosystem tooling such as PyTorch/TensorFlow/Hugging Face, MLFlow, WnB, Feast, and AI/ML-related AWS/GCP managed services (VertexAI, SageMaker).
- Excellent communication & partnership skills, able to translate complex system design into intuitive developer-facing abstractions.
- Desirable. Familiarity with data and AI/ML platform approaches, technologies and open-source contributions in media technology companies.
- Desirable. Knowledge of multimodal AI/ML (audio, video, text) data preparation, feature extraction, model development, training, and evaluation workflows.
- Desirable. Knowledge of LLM/foundation model sizing/estimation, training requirements, evaluation workflows and orchestration and deployment patterns.
- Desirable. Experience designing feature stores or embedding services tightly integrated with training pipelines.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr Manager , Data & AI Platform (Bengaluru)
🏢 Dolby
📍 Bengaluru