Senior Manager, Data & AI Platform
Bengaluru, KA, IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingSet a multi-year roadmap for data pipelines, AI/ML workflows and compute orchestration
Build APIs, SDKs and developer tools for end-to-end AI/ML pipelines
Abstract engines like Spark, Ray and Kubernetes into secure, governed workflows
Make AI/ML lifecycle workflows versioned and reproducible, with full lineage
Partner on observability, monitoring and incident response for ML systems
From the employer’s posting
Set a multi‑year platform roadmap that integrates data pipelines, AI/ML workflows, and compute orchestration layers
Deliver robust APIs, SDKs and developer friendly tools and interfaces (CLIs, GUIs, dashboards, etc)
Build a unified platform that abstracts complex underlying engines (Spark, Ray, Kubernetes, Airflow/Flyte/Metaflow, etc.)
can be orchestrated via consistent, versioned workflows with full lineage and reproducibility
Partner with platform engineering/MLOps and infrastructure to define observability stacks
Education & alternatives
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
Tools in this posting
- AWS
- GCP
- Kubernetes
- MLflow
- SageMaker
- Spark
- Airflow
- Hugging Face
- PyTorch
- TensorFlow
Source — Tool mentions in context
* 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, MLOps stack: experiment tracking, feature stores, model registries/lineage (MLFlow, WnB, Feast, etc), and AI/ML-related AWS/GCP managed services (VertexAI, SageMaker, etc) * Excellent communication & partnership skills, able to translate complex system design into intuitive developer-facing abstractions
* 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.
* Strong 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, MLOps stack: experiment tracking, feature stores, model registries/lineage (MLFlow, WnB, Feast, etc), and AI/ML-related AWS/GCP managed services (VertexAI, SageMaker, etc)
Posting record
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- Live
- First seen by us
- Aug 25, 2026 · 67 days ago
- Recorded sightings
- 97
- Last seen by us
- Oct 30, 2026
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Bengaluru, KA, IN
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