Senior AI/ML Engineer

Design, develop, and deploy AI/ML models to solve complex business problems.

Build and optimize machine learning and deep learning algorithms using real-world datasets.

Develop Generative AI applications using Large Language Models (LLMs), RAG, prompt engineering, and vector databases.

Implement AI-powered applications using frameworks such as LangChain, LangGraph, and LlamaIndex.

Develop and integrate REST APIs and microservices for AI/ML solutions.

Work with structured and unstructured data for data preprocessing, feature engineering, and model evaluation.

Implement AI agents and agentic workflows using tools, APIs, and enterprise data sources.

Deploy and monitor AI/ML models using MLOps practices and CI/CD pipelines.

Leverage cloud platforms such as AWS, Azure, or Google Cloud for AI model development and deployment.

Collaborate with data engineers, software developers, architects, and business stakeholders.

Ensure AI solutions meet performance, scalability, security, reliability, and responsible AI standards.

We are looking for an experienced Senior AI/ML Engineer with 10+ years of experience in designing, developing, and deploying scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in Python, machine learning, deep learning, Generative AI, LLMs, and cloud-based AI services., 10+ years of experience in software engineering, AI/ML engineering, or related fields.

Strong programming experience in Python and AI/ML libraries.

Hands-on experience with machine learning, deep learning, NLP, and statistical modeling.

Experience with TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.

Strong understanding of Generative AI, LLMs, RAG architecture, and prompt engineering.

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

Knowledge of AI agent frameworks such as LangChain, LangGraph, or CrewAI.

Experience building and integrating REST APIs and scalable AI applications.

Hands-on experience with AWS, Azure, or Google Cloud Platform AI/ML services.

Knowledge of Docker, Kubernetes, Git, CI/CD, and MLOps tools.

Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

Experience with multi-agent systems, Model Context Protocol (MCP), and enterprise AI integrations.

Knowledge of fine-tuning, model evaluation, inference optimization, and guardrails.

Experience with data pipelines, SQL, Spark, and large-scale data processing.