Live opening · Posted 7 hours ago

Lead AI/ML Engineer

LeadSquared · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 7 hours ago
CompanyLeadSquared
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SkillsPython, AWS, Azure, GCP, Docker, Pandas, TensorFlow
SourceLinkedin
ListedPosted 7 hours ago

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About the role

Description supplied by the original job listing.

Job Description – Lead AI/ML Engineer
14 Oct 2026
@Shruti
Experience: 4–6 years
Type: Full-time
Location: Bengaluru
About The Role
We are hiring a hands-on Lead AI/ML Engineer to design, build and ship production AI systems, from agentic LLM applications to classical ML models. You will own solutions end to end, guide a small team, and turn business problems into reliable AI products.
Key Responsibilities
Design and build agentic AI systems with planning, tool calling, memory and multi-agent workflows using LangChain and LangGraph.
Architect and optimise RAG pipelines: chunking, embeddings, vector search, re-ranking and evaluation.
Build, train and deploy traditional ML and deep learning models with scikit-learn, PyTorch and TensorFlow.
Write production-grade Python, expose models as APIs, and deploy on cloud with MLOps best practices.
Lead and mentor ML/AI engineers, review code and designs, and partner with product and business teams.
Required skills
4–6 years of overall experience, including at least 1–2 years building LLM or GenAI applications.
Expert-level Python (NumPy, Pandas, FastAPI, async).
Hands-on experience with Agentic AI, LangChain, LangGraph and RAG.
Practical experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, Chroma or FAISS.
Strong traditional ML skills with scikit-learn, PyTorch and TensorFlow, plus solid statistics and model evaluation.
Working knowledge of Git, Docker and a cloud platform (AWS, Azure or GCP).
Bachelor's or master's degree in computer science, AI, Data Science or a related field.
Nice to have
LLM fine-tuning (LoRA/QLoRA), LLM evaluation tools (LangSmith, Ragas) and MLOps tools (MLflow, SageMaker).

Work arrangement
No

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