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AI/ML Engineer

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artificial-intelligencegenerative-aillmragmachine-learningpythonazureopenailangchaindatabricksmlflowmlopsvector-databasesprompt-engineeringai-safetyrest-apipineconeci/cddevopsdata-science

Job Description – AI/ML Engineer – Generative AI & LLM

Job Title: AI/ML Engineer – Generative AI
Experience: 3–6 Years
Employment Type: Full-Time

Job Summary

We are looking for an experienced AI/ML Engineer with strong expertise in Generative AI, Large Language Models (LLMs), RAG, and Machine Learning. The ideal candidate should have hands-on experience developing and deploying AI solutions using Python, Azure OpenAI, LangChain, Semantic Kernel, Databricks, MLflow, and MLOps practices.

Key Responsibilities

- Design, develop, and deploy Generative AI and LLM-based applications.

- Build RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector search, document processing, and semantic retrieval.

- Develop AI/ML solutions using Python and machine learning frameworks.

- Work with Azure OpenAI to integrate and customize LLM-based solutions.

- Develop LLM applications and AI workflows using LangChain and Semantic Kernel.

- Implement prompt engineering, evaluation, optimization, and LLM application best practices.

- Build and maintain MLOps pipelines for model development, deployment, monitoring, and lifecycle management.

- Use Databricks for data processing, machine learning, and AI workloads.

- Implement experiment tracking, model management, and deployment workflows using MLflow.

- Collaborate with data engineers, software developers, and business teams to integrate AI solutions into enterprise applications.

- Troubleshoot and optimize AI/ML models and applications for performance, scalability, reliability, and cost.

- Follow responsible AI, security, governance, and data privacy best practices.

Required Technical Skills

- Python

- Generative AI & LLMs

- RAG Architecture

- Machine Learning

- Azure OpenAI

- LangChain

- Semantic Kernel

- MLOps

- Databricks

- MLflow

- Prompt Engineering

- Embeddings & Vector Search

- Model Evaluation and Optimization

- REST APIs and AI application integration

Good to Have

- Experience with Azure AI services and cloud-based AI architectures.

- Knowledge of vector databases such as Azure AI Search, Chroma, Pinecone, or FAISS.

- Experience with LLM evaluation, guardrails, and Responsible AI.

- Knowledge of CI/CD and DevOps practices for AI/ML workloads.

- Experience working in enterprise AI projects.

Education

Bachelor’s/Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Work Location: Remote

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