NC
AI Engineer / Data Scientist
NR Consulting - India
🇮🇳 India
On-site
1 week ago
- AI
- Machine Learning
- RAG
- MLOps
- AWS
- Azure
- GCP
- Python
- Core Data
- Pandas
- NumPy
- scikit-learn
- PyTorch
- TensorFlow
- LangChain
- LlamaIndex
- Pinecone
- Milvus
- Chroma
- Hugging Face
- Docker
- REST API
- FastAPI
- Git
- CI/CD
1 week ago
Location: Mumbai
Exp: 3-5 Yrs
Job Description:
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 & Modern 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 · NR Consulting - India