AI/ML Engineer

Job Summary

We are seeking a skilled AI/ML Engineer to design, develop, and deploy machine learning and generative AI solutions. The ideal candidate will have strong experience in Python, SQL, REST APIs, deep learning frameworks such as PyTorch and TensorFlow, and hands-on expertise with Large Language Models (LLMs) including Anthropic Claude and Google Gemini. Experience building Retrieval-Augmented Generation (RAG) systems and production-grade AI applications is highly desirable.

Key Responsibilities

• Design, develop, and deploy machine learning and generative AI solutions for business applications.

• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.

• Integrate and work with LLMs such as Anthropic Claude, Google Gemini, and other foundation models.

• Develop RESTful APIs for AI/ML services and model inference.

• Fine-tune, evaluate, and optimize machine learning and deep learning models.

• Create scalable data pipelines for training, inference, and monitoring.

• Collaborate with product managers, data engineers, and software developers to deliver AI-powered products.

• Perform prompt engineering, model evaluation, and experimentation to improve AI system performance.

• Monitor deployed models for accuracy, latency, and reliability.

• Document AI solutions, architecture, and best practices.

Required Skills & Qualifications

• Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, or related field.

• Strong programming experience in Python.

• Proficiency in SQL and database design concepts.

• Experience developing and consuming REST APIs.

• Hands-on experience with PyTorch and/or TensorFlow.

• Experience building and deploying machine learning models in production environments.

• Strong understanding of NLP, deep learning, and transformer architectures.

• Experience working with Large Language Models (LLMs), including Anthropic Claude and Google Gemini.

• Knowledge of Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.

• Familiarity with Git, CI/CD pipelines, and software engineering best practices.

• Strong problem-solving and analytical skills.

Preferred Qualifications

• Experience with vector databases such as Pinecone, Weaviate, Chroma, or FAISS.

• Knowledge of LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.

• Familiarity with Docker, Kubernetes, and MLOps practices.

• Experience with model monitoring, observability, and AI evaluation frameworks.

• Understanding of prompt engineering, agentic workflows, and multi-agent systems.

Nice to Have

• Experience with fine-tuning open-source LLMs.

• Knowledge of multimodal AI applications.

• Exposure to model serving frameworks such as TorchServe, Triton, or vLLM.

• Contributions to open-source AI/ML projects.