Title: AI Engineer / Data Scientist

Location: Mumbai

Exp: 3-5 Yrs

:

Key Responsibilities

● GenAI & AI Solution Development: Design and deploy modern Generative AI solutions, including Large Language Model (LLM) integrations, Retrieval-Augmented Generation (RAG) pipelines, prompt engineering, and agentic workflows.

● Production Systems & MLOps: Build, containerize, and deploy scalable machine learning inference pipelines and APIs into production environments. Monitor, optimize, and troubleshoot model performance, latency, and costs in cloud environments.

● Model Development & Experimentation: Apply a strong functional understanding of machine learning and deep learning algorithms. Perform exploratory data analysis, feature engineering, fine-tuning, and rigorous model evaluation.

● Cloud Infrastructure (CSP): Leverage cloud services (AWS, Azure, or GCP) to architect robust data and AI workflows, utilizing managed AI services, container registries, and serverless/compute instances.

● Cross-Functional Collaboration: Partner closely with software engineering, product, and data teams to seamlessly integrate AI capabilities into customer-facing applications.

Required Qualifications & Skills

● Experience: 3–5 years of professional experience in data science, machine learning, or AI engineering, with a proven track record of shipping systems to production.





● Programming: Advanced, hands-on proficiency in Python and its core data/ML libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch or TensorFlow).

● Generative AI & Contemporary AI Tools: Hands-on experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex), vector databases (e.g., Pinecone, Milvus, Chroma), and Hugging Face ecosystems.

● Cloud Platforms (CSP): Solid working knowledge of at least one major cloud provider—AWS, Microsoft Azure, or Google Cloud Platform (GCP)—for deploying and managing AI workloads.

● Production & Software Engineering Mindset: Familiarity with Docker/containerization, REST API development (FastAPI), Git version control, and CI/CD pipelines.

● Core Fundamentals: Strong functional understanding of model development lifecycles, statistical evaluation metrics, data preprocessing, and overcoming common production pitfalls (like data drift or latency bottlenecks).

Preferred Qualifications

● Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.

● Experience fine-tuning open-source LLMs or implementing advanced RAG optimizations.

● Certifications from AWS, Azure, or GCP in Machine Learning or Cloud Architecture.

📌 AI Engineer / Data Scientist (Mumbai)
🏢 NR Consulting
📍 Mumbai