Team Lead - AI / ML
Bangalore, Karnataka, IndiaJobNo compensation foundPosted 8mo agoVerified open 2 days ago
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At a glance
Compensation
No compensation found
Location
Bangalore, Karnataka, India
Work Authorization
Not specified
Job overview
The Team Lead will head a small, high‑velocity AI/ML group to design, build, and ship ML and GenAI products end‑to‑end, handling problem framing, modeling, scalable deployment, and monitoring while aligning technical roadmaps with product goals.
Skills & qualifications
RequiredNice to have
Skills
MentorshipPythonArtificial IntelligenceContainersAmazon Web ServicesInfrastructure as Code (IaC)ObservabilityQuality AssuranceAPI DevelopmentGovernanceUnsupervised Learning TechniquesMachine LearningModelingPackagingTechnical LeadershipNeo4jPyTorchOrchestrationHuggingFaceLangChainMilvusAWSMLOpsTransformer ArchitecturesPrompt EngineeringKnowledge Graph DesignNeo4j Schema ModelingLLM Fine-TuningLoRA/QLoRAPEFTQuantizationStartup Experience
Qualifications
5+ Years Experience1+ Year Technical Leadership Experience
Full job description
Lead a small, high-velocity team to design, build, and ship ML and GenAI products end-to-end, from problem framing and modeling to scalable deployment and monitoring.
Responsibilities:
- Own the technical roadmap for ML/GenAI initiatives and align it with product goals and delivery timelines.
- Lead LLM workflow and agentic system design, including retrieval, tool-use, and evaluation pipelines.
- Guide model development using PyTorch and HuggingFace; enforce code quality, testing, and model evaluation standards.
- Oversee MLOps: CI/CD for models, API design, containerization, orchestration, and cost/performance optimization on AWS.
- Collaborate with product, data, and infra teams; run experiments, A/B tests, and error analysis.
- Mentor engineers, conduct code/model reviews, and grow team capabilities.
Requirements:
- At least 5 years of experience with a minimum of one year in technical leadership leading projects or teams.
- General AI/ML Team Lead requirements: roadmap ownership, sprint planning, stakeholder communication, mentoring, and setting engineering best practices.
- Strong Python understanding: idiomatic code, testing, packaging, async I/O, performance profiling.
- Strong ML, DL, and GenAI understanding: supervised/unsupervised learning, transformer architectures, prompt engineering, evaluation, and safety/guardrails.
- Experience building LLM-based workflows and agents, including retrieval (RAG), tools, memory, and evaluation loops.
- Hands-on experience with LangChain, HuggingFace, PyTorch, Neo4j, Milvus, and AWS for scalable, production-grade systems.
- MLOps experience: model deployments, API development, observability, infra management (containers, orchestration, IaC), and data/version governance.
Preferred Qualifications:
- Knowledge graph design and Neo4j schema modeling for semantic retrieval and reasoning.
- LLM fine-tuning with deployment to production: LoRA/QLoRA, PEFT, quantization, evaluation, rollback strategies, and cost optimization.
- Startup experience: comfort with ambiguity, rapid iteration, and owning outcomes across the stack.
You've read the whole posting — now see how you match it.