Job Description

About the Role

We are seeking a highly skilled and innovative

Senior Data Scientist - AI/ML

to lead the design, development, and deployment of

advanced machine learning models and AI solutions. This role is ideal for professionals with a strong foundation in data science,

deep learning, and statistical modeling who can drive business impact through data-driven strategies and products.

Key Responsibilities:

Design, build, and deploy machine learning and AI models for a variety of business use cases. Lead end-to-end ML projects from ideation to production, including data preparation, feature engineering, model training, validation, and monitoring. Collaborate with engineering, product, and business stakeholders to understand requirements and deliver impactful solutions. Leverage techniques in deep learning, NLP, generative AI, time-series analysis, or computer vision, as needed. Mentor junior data scientists and contribute to technical best practices, code reviews, and solution architecture. Evaluate and implement ML Ops practices for scalable and maintainable deployment. Stay updated on emerging trends in AI/ML and drive innovation by applying cutting-edge research.

Requirement:

6+ years of experience in

data science, machine learning

, and

AI model development

. Proficiency in

Python, SQL

, and ML frameworks such as

scikit-learn, TensorFlow, PyTorch

, or

XGBoost

. Experience with cloud platforms (AWS/GCP/Azure) and data pipeline tools (Airflow, Spark, etc.). Strong knowledge of

model evaluation, A/B testing, feature selection,

and

data preprocessing.

Excellent communication and storytelling skills to present findings to both technical and non-technical audiences. Experience in GenAI frameworks (OpenAI, Vertex AI), multi-agent architectures, and MLOps tooling. Ability to ship high-quality intelligent products quickly and at scale.

Tech Stack:

Languages & Frameworks:

Python, Java, SQL, JavaScript/TypeScript TensorFlow, PyTorch, Scikit-learn,Spring Boot React, Angular

Cloud Platform:

GCP - Vertex AI, BigQuery, Cloud Functions, Cloud Run, Dataflow, Pub/Sub OCI - Data Science, Autonomous Data Warehouse, Functions, Container Engine for Kubernetes (OKE), Data Flow, and
Streaming

Data & MLOps:

BigQuery, AlloyDB, MongoDB, Redis Any relation Database - Oracle , MySQL, MSSQL Any of the MLOps - MLflow, Kubeflow, Airflow Docker, Kubernetes

GenAI & Agents:

Vertex AI Gemini, OpenAI, Claude LangChain, LlamaIndex, FAISS, Pinecone RAG pipelines, autonomous agents, multi-agent orchestration, memory modules, tool use, prompt chaining

Dev Tools:

* GitHub Copilot, ChatGPT, Cursor AI