Data Scientist

Overview

🚀 Hiring: Data Scientist – L3 (ML & GenAI)

📍 Location: Bangalore

🏢 Work Mode: Hybrid (WFO)

💼 Job Type: Full-Time

⏳ Experience: 6–9 Years

Role Overview

We are looking for a Data Scientist – L3 to lead the design, development, and deployment of advanced ML and GenAI solutions. This is a senior individual contributor role, ideal for professionals who enjoy owning end-to-end AI systems and solving ambiguous, high-impact problems.

You will work closely with engineering, product, and business teams to build LLM-powered applications that integrate seamlessly into client products.

Key Responsibilities

ML & Data Science Leadership

Lead development of ML solutions across supervised, unsupervised, and time-series problems

Design and own feature engineering, training, evaluation, and monitoring

pipelines

Apply advanced experimentation, error analysis, and iterative model improvements aligned with business KPIs

LLM & GenAI System Development

Design and implement GenAI-powered systems such as copilots, document processors, summarization agents, and intelligent assistants

Build workflows using prompt engineering, RAG pipelines, context management, and hybrid model chaining

Lead LLM fine-tuning initiatives using:

Instruction tuning

Parameter-efficient methods (LoRA, QLoRA, PEFT)

Full-model fine-tuning for domain-specific use cases

Evaluate and optimize LLM providers (open-source vs API-based) for performance, cost, and latency

Collaboration & Impact

Partner with engineering, product, and business stakeholders to shape technical direction

Support pre-sales efforts, PoC development, and client workshops as a technical SME

Ensure technical excellence and best practices across the data science lifecycle

Mentorship & Technical Leadership

Mentor junior and mid-level data scientists on modeling, GenAI architecture, and experimentation

Lead internal knowledge-sharing sessions on ML and LLM advancements

Contribute to building strong AI capabilities within the team

Required Skills & Qualifications

6–9 years of hands-on experience in Data Science, Machine Learning, or AI product development

Strong Python skills with expertise in:

pandas, NumPy, scikit-learn

XGBoost / LightGBM

Proven experience deploying ML models to production (batch or real-time)

Hands-on experience with LLMs (OpenAI, Mistral, Claude, LLaMA)

Experience using LangChain, LlamaIndex, or similar frameworks

Direct experience in LLM fine-tuning using Hugging Face Transformers, PEFT, or custom pipelines

Strong understanding of:

Prompt engineering

Embeddings & similarity search

Vector databases (FAISS, Pinecone, etc.)

Experience with Docker, Git, and cloud platforms (AWS, GCP, or Azure)

Good to Have

Exposure to MLOps / GenAI platforms (MLflow, SageMaker, Weights & Biases)

Experience with GenAI evaluation and safety frameworks

Open-source contributions or strong personal projects in ML/LLMs