SI
Full time
🤖 AI / ML
Principal ML Engineer (MLOps Lead) at Signify
Listed by DevShelfHub
Bangalore, India
Hybrid
Senior · 12–16 yrs
About the Role
Signify is hiring a Principal ML Engineer / MLOps Lead in Bangalore to lead design, engineering, and productionization of enterprise ML, GenAI, and agentic AI platforms across AWS and Snowflake.
This role owns end-to-end ML engineering from data pipelines through monitoring, governance, reliability, cost control, and reuse across markets and business functions.
What you'll do
- Lead ML engineering and MLOps for Signify Advanced Analytics enterprise platforms.
- Building GenAI and agentic AI systems with RAG, tool-using agents, and guardrails
- Leading ML engineering architecture, delivery standards, and platform adoption
- Owning productionization of ML and GenAI solutions across business functions
- Designing scalable ML pipelines across training, deployment, monitoring, and retirement
- Defining target architecture for enterprise GenAI platforms and agent registries
- Engineering reliable agent runtimes with tracing and production SLOs
- Designing evaluation frameworks for ML, GenAI, and agentic AI systems
- Establishing LLMOps practices and optimizing GenAI workloads for cost and latency
- Building reusable AI platform services, APIs, and integration patterns
- Creating observability dashboards for drift, agent traces, and business impact
What we're looking for
- B.Tech/Masters in Computer Science, Computer Engineering, Data Science, or equivalent
- 12+ years in ML engineering, MLOps, advanced analytics, or applied data science
- Strong hands-on Python and SQL with ML libraries and frameworks
- Practical GenAI and agentic AI platform engineering experience
Skills & Technologies
Required
B.Tech/Masters in Computer Science, Computer Engineering, Data Science, or equivalent
12+ years in ML engineering, MLOps, advanced analytics, or applied data science
Strong hands-on Python and SQL with ML libraries and frameworks
Practical GenAI and agentic AI platform engineering experience
AWS services: SageMaker, Bedrock, Lambda, Fargate, EC2, S3, SNS, SQS
Snowflake integration with Snowpark, APIs, and Cortex
CI/CD for ML, model versioning, automated testing, and deployment gates
LLMOps, prompt testing, model evaluation, and responsible AI practices
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- Own enterprise GenAI and agentic AI platform architecture across AWS and Snowflake with LLMOps, observability, and responsible AI at a global connected lighting leader.
- Build and operate GenAI and agentic AI with RAG, embeddings, vector search, and multi-agent orchestration
- Lead ML engineering and MLOps including architecture, delivery standards, and production support
- Productionize ML and GenAI across forecasting, MMM, segmentation, contract intelligence, and copilots
- Design scalable ML pipelines from ingestion through model retirement
- Define enterprise GenAI platform architecture with agent registry and MCP registry
- Engineer reliable agent runtimes with retry logic, fallbacks, and production SLOs
- Establish LLMOps practices for prompt testing, evaluation, and safety testing
- Integrate with Snowflake (Snowpark, Cortex) and AWS (SageMaker, Bedrock, Lambda)
- Guide ML engineers on architecture, evaluation, and operational excellence
- Champion responsible AI: explainability, fairness, transparency, and auditability
About Signify
Signify transforms the lighting industry through IoT, data analytics, and AI-powered smart solutions. The AI & Advanced Analytics team in Bangalore builds enterprise-scale ML and GenAI platforms supporting forecasting, marketing mix modeling, customer segmentation, contract intelligence, and enterprise copilots.
- Industry
- Technology
- Company Size
- 500+
- Website
- signify.com
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Job Details
- Type
- Full time
- Level
- Senior
- Experience
- 12–16 years
- Location
- Bangalore, India
- Work Mode
- Hybrid
- Category
- AI / ML
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