Key Responsibilities

Model Development & Deployment

- Design, develop, and optimize machine learning and deep learning models
- Work on supervised, unsupervised, and reinforcement learning use cases
- Deploy models into production using scalable APIs and microservices
- Optimize models for performance, latency, and cost

Generative AI & LLMs

- Build and integrate solutions using LLMs (e.g., OpenAI, open-source models)
- Implement RAG (Retrieval-Augmented Generation) pipelines
- Fine-tune models and design prompt engineering strategies
- Develop AI agents and workflow automation systems

Data Engineering & Processing

- Collect, clean, and preprocess structured and unstructured data
- Build feature engineering pipelines
- Work with large-scale datasets and distributed systems

MLOps & Lifecycle Management

- Implement CI/CD pipelines for ML models
- Monitor model performance, drift, and retraining needs
- Use tools for experiment tracking, versioning, and model governance

Collaboration & Stakeholder Interaction

- Work closely with product managers, engineers, and business stakeholders
- Translate business requirements into technical AI solutions
- Present findings and model performance to leadership

Required Skills

Core AI/ML Skills

- Strong experience in machine learning algorithms and statistical modeling
- Hands-on experience with deep learning frameworks (TensorFlow / PyTorch)
- Experience with NLP, Computer Vision, or Time-Series models





Generative AI

- Experience with LLMs, prompt engineering, and RAG architectures
- Familiarity with frameworks like LangChain, LlamaIndex, or LangGraph
- Understanding of embeddings, vector databases (FAISS, Pinecone, etc.)

Programming & Tools

- Strong programming in Python
- Experience with libraries: scikit-learn, pandas, NumPy, Hugging Face
- Knowledge of REST APIs, FastAPI/Flask
- Experience with Docker, Kubernetes (preferred)

Cloud & Platforms

- Hands-on experience with AWS / GCP / Azure
- Familiarity with ML services like SageMaker, Vertex AI, or Azure ML

Qualifications

- Bachelors/Master’s degree in Computer Science, AI, Data Science, or related field
- Relevant certifications in AI/ML or Cloud (preferred)

Preferred Experience

- Experience in BFSI / FinTech / Healthcare domains
- Working with sensitive or regulated data environments
- Exposure to real-time AI systems and high-scale deployments

Key Competencies

- Robust problem-solving and analytical thinking
- Ability to work independently and in cross-functional teams
- Good communication and presentation skills
- Ownership mindset and attention to detail

Nice to Have

- Experience with AI agents / autonomous systems
- Knowledge of model explainability (SHAP, LIME)
- Familiarity with data privacy, compliance, and security standards
- Experience in building AI platforms or internal tools

📌 Data Scientist (Karnataka)
🏢 Aziro
📍 Karnataka