Sr AI Engineer

Job Title: AI/ML Engineer

Experience Level: 1-6 years
Location: [Pune]
Type: Full-Time

Job Summary

We are looking for a dynamic and innovative AI/ML Engineer with expertise in Generative AI and hands-on experience in GCP or other cloud platforms. The ideal candidate will have proven experience in developing, training, fine-tuning, and deploying advanced AI/ML models. You will play a pivotal role in building scalable, production-ready solutions involving large datasets, NLP techniques, and cutting-edge frameworks such as MCP, Retrieval-Augmented Generation (RAG), and REACT (Retrieve, Extract, Adapt, Construct, Think).

This role requires a solid foundation in Python, SQL, and AI/ML development pipelines, combined with a passion for solving real-world problems using AI.

Roles & Responsibilities

1. Model Development & Training
• Design, train, and fine-tune AI/ML models, especially Generative AI and Large Language Models (LLMs), to address specific use cases.
• Build conversational AI solutions and chatbots using frameworks such as LangChain, RAG (Retrieval-Augmented Generation), and Chain-of-Thought (COT) prompting.
• Apply advanced techniques, including embeddings, fine-tuning, and custom prompting strategies.
• Incorporate REACT (Retrieve, Extract, Adapt, Construct, Think) methods to enhance model capabilities.
• Develop scalable AI solutions to integrate seamlessly into production environments.
2. Data Handling
• Manage large-scale datasets for AI/ML applications, ensuring data quality, transformation, and normalization.
• Conduct data analysis, preprocessing, and munging to extract valuable insights.
• Implement scalable data engineering workflows for model development and production.
3. Cloud AI/ML Deployment
• Deploy, manage, and optimize AI models on Google Cloud Platform (GCP) (or other cloud platforms like AWS/Azure).
• Leverage GCP services such as Vertex AI, BigQuery, Cloud Functions, and Dataflow for AI workflows.
4. Collaboration & Solutioning
• Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to deliver AI-driven solutions.
• Integrate models with client-facing applications, ensuring end-to-end implementation.
• Support scalable development through Docker for containerization (a plus).
5. Continuous Improvement
• Stay updated with the latest advancements in AI, ML, and Generative AI frameworks, tools, and methodologies.
• Proactively learn new technologies and apply them to improve processes and solutions.
6. Web Scraping (Optional but Preferred)
• Implement web scraping solutions to gather data from unstructured sources for model training and validation
• .

Required Skills & Qualifications

• 3-6 years of experience in AI/ML model development, training, and fine-tuning.
• Strong programming skills in Python and SQL.
• Hands-on experience with Generative AI, LLMs, and NLP techniques.
• Experience working with LangChain, RAG frameworks, and advanced prompting strategies.
• Proficiency in Chain-of-Thought (CoT) prompting, Model Context Protocol (MCP), and Agent-to-Agent (A2A) orchestration
• Proficiency in embeddings and fine-tuning models for specific tasks.
• Strong understanding of machine learning algorithms and statistical analysis.
• Experience working with large datasets and scalable data processing workflows.
• Hands-on experience with GCP (Vertex AI, BigQuery) or other cloud platforms (AWS/Azure).
• Knowledge of Docker for deployment and containerization.
• Solid skills in data cleaning, transformation, and normalization for data integrity.

Preferred Skills

• Familiarity with Reinforcement Learning from Human Feedback (RLHF).
• Understanding of COT (Chain-of-Thought) prompting.
• Proficiency in REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks.
• Experience in web scraping techniques.

Key Attributes

• Strong analytical and problem-solving abilities.
• Ability to work independently as well as collaboratively in a team environment.
• Excellent communication skills to interact with stakeholders and cross-functional teams.
• Proactive attitude to learn and adopt new AI technologies and frameworks.