LEAD DATA SCIENCE (ML Ops)
At a glance
Senior ML Platform & Ops role at TE Connectivity. Bangalore.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Shape and maintain the Databricks ML environment, connecting its platform components with AWS services
- Set shared rules for delivery pipelines, testing, model releases and reproducible work across teams
- Automate model training, checks, rollout and retraining, then track performance, drift, latency and cost
- Oversee model lineage, permissions and audit records while tuning compute use and spend
- Guide engineers through reviews and incident follow-up, and assess whether new tools are worth adopting
What you bring
- You have production experience with MLflow, Unity Catalog, Delta Lake and Databricks Workflows or Jobs
- You can build scalable data and feature pipelines with Spark or PySpark, and write tested production Python
- You bring infrastructure-as-code and CI/CD experience, plus Docker and Kubernetes skills
- You have hands-on experience with AWS services and Databricks networking and security
- You have implemented batch and real-time inference, model monitoring, deployment controls and feature-store or streaming systems
Who this fits
This is a senior ML platform role for someone who can set technical standards while mentoring engineers and responding to incidents. The work centers on Databricks and AWS, with Kubernetes and Kafka or Kinesis identified as must-have capabilities.
From the employer
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
Job Overview
Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods, such as machine learning. It often involves synthesizing large volume of information and extracting signals from data in a programmatic way.Job Responsibilities
• Architect and evolve the ML platform on Databricks (Unity Catalog, MLflow, Feature Store, Model Serving, Workflows) integrated with AWS services
• Define and enforce standards for CI/CD, testing, model promotion, and reproducibility across teams
• Build automated pipelines for training, validation, deployment, and retraining
• Implement monitoring for model performance, data drift, latency, and cost (Lakehouse Monitoring, CloudWatch, Prometheus/Grafana, or similar)
• Own governance: model lineage, access control, audit trails, and compliance with data and regulatory requirements
• Manage compute and cost optimization (cluster policies, GPU usage, serving autoscaling)
• Mentor engineers, run design and code reviews, and drive incident response and postmortems
• Evaluate and introduce new tooling where it earns its place
Required Skills
Databricks
• Production experience with MLflow (tracking, registry, model serving), Unity Catalog, Delta Lake, and Databricks Workflows/Jobs
• Databricks Asset Bundles or Terraform provider for workspace and job deployment
• Spark/PySpark for scalable data and feature pipelines
• Cluster configuration, policies, and performance tuning
AWS
• Core services: S3, IAM, VPC, EC2, ECR, Lambda, CloudWatch, Secrets Manager, KMS
• Databricks-on-AWS networking and security (PrivateLink, cross-account roles, workspace setup)
• Familiarity with SageMaker, EKS, or API Gateway as complements to Databricks serving
Engineering and DevOps
• Strong Python; clean, tested, production-grade code
• Infrastructure as Code (Terraform strongly preferred)
• CI/CD (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps)
• Docker; Kubernetes is a must
MLOps practices
• Batch and real-time inference patterns
• Drift detection, A/B and shadow deployment, rollback strategies
• Experiment tracking, model versioning, and reproducibility
• LLMOps on Databricks: Mosaic AI, Vector Search, RAG pipelines, evaluation and guardrails
• Feature store design and streaming (Structured Streaming, Must have: Kafka/Kinesis)
• Databricks or AWS certifications (ML Professional, Solutions Architect)
• FinOps experience and regulated-industry or data-residency exposure
ABOUT TE CONNECTIVITY
TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence, and more.
Our more than 90,000 employees, including 10,000 engineers, work alongside customers in approximately 130 countries. In a world that is racing ahead, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn, Facebook, WeChat, Instagram and X (formerly Twitter).
WHAT TE CONNECTIVITY OFFERS:
We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority!
• Competitive Salary Package
• Performance-Based Bonus Plans
• Health and Wellness Incentives
• Employee Stock Purchase Program
• Community Outreach Programs / Charity Events
• Employee Resource Group
IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD
TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com. If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities.
Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.