Data Scientist-AIML Engineer

Job Description: Senior Engineer GenAI / Machine Learning / Python / AWS

Experience: 5–7 Years
Location: [Add Location / Remote / Hybrid]

Role Overview

We are seeking a highly skilled Senior Engineer with strong expertise in Generative AI (GenAI), Machine Learning, Python, and AWS. The ideal candidate will design, build, and deploy scalable AI/ML solutions, including Generative AI applications leveraging LLMs, while ensuring performance, reliability, and production readiness.

Key Responsibilities

1. GenAI & ML Model Development

• Design and develop machine learning and Generative AI solutions for real-world business problems.
• Build applications using Large Language Models (LLMs) such as GPT, Llama, etc.
• Implement RAG (Retrieval-Augmented Generation) pipelines.
• Fine-tune or adapt pre-trained models where applicable.

2. Application Development (Python)

• Develop robust backend services and pipelines using Python.

• Work with libraries and frameworks such as:

• TensorFlow, PyTorch, Scikit-learn

• LangChain, LlamaIndex (preferred)

• Build APIs to expose ML/GenAI capabilities.

3. Cloud & AWS Implementation

• Design and deploy ML/AI solutions on AWS cloud platform.

• Work with services such as:

• SageMaker

• Lambda

• S3, EC2, RDS

• API Gateway

• Bedrock (for GenAI) – preferred

• Ensure scalability, monitoring, and cost optimization of AI workloads.

4. Data Engineering & Processing

• Work with structured and unstructured data.
• Build data pipelines, preprocessing, and feature engineering workflows.
• Ensure high-quality datasets for model training and validation.

5. Model Deployment & MLOps

• Deploy models into production using MLOps practices.
• Implement CI/CD for ML pipelines.
• Monitor model performance, drift, and retraining needs.
• Use tools like Docker, Kubernetes, MLflow (good to have).

6. System Design & Integration

• Design scalable AI/ML architectures integrated with enterprise systems.
• Collaborate with product and engineering teams to embed AI capabilities.
• Ensure security, compliance, and responsible AI practices.

7. Research & Innovation

• Stay updated with the latest advancements in GenAI and ML.
• Evaluate new tools, models, and frameworks.
• Drive innovation and proof-of-concepts (POCs).

Required Skills

Core Technical Skills

• Strong experience in:

• Python programming

• Machine Learning algorithms and concepts

• Generative AI / LLM-based applications

• Hands-on experience with:

• PyTorch / TensorFlow / Scikit-learn

• LangChain / LLM orchestration frameworks

• Experience in building and deploying REST APIs.

Cloud & DevOps

• Strong experience with AWS services for ML and application deployment.

• Knowledge of:

• CI/CD tools

• Containerization (Docker)

• Orchestration (Kubernetes – plus)

Data Skills

• Experience with:

• Data preprocessing and feature engineering

• SQL / NoSQL databases

• Handling large-scale datasets

Preferred Skills

• Experience with:

• RAG architectures and vector databases (Pinecone, FAISS, OpenSearch)

• Prompt engineering and prompt optimization

• Fine-tuning LLMs

• Knowledge of:

• Responsible AI, AI governance

• Model explainability tools

Soft Skills

• Strong analytical and problem-solving mindset.
• Excellent communication and stakeholder management.
• Ability to work independently and lead technical initiatives.
• Innovative thinking and curiosity for emerging technologies.

Educational Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field.e & responsibilities