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Two95 International

GenAI / AI-Machine Learning Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeGurugram, Haryana, IndiaNo salary listed

About the Job

Requirements

  • Strong hands-on experience in Python and strong working knowledge of SQL.
  • Experience developing REST APIs using FastAPI or similar Python frameworks.
  • Good understanding of object-oriented programming, modular development, testing, and software-engineering best practices.
  • Experience working in Agile development environments.
  • Hands-on experience with Scikit-learn, TensorFlow, PyTorch, and Keras.
  • Strong understanding of regression, classification, clustering, feature engineering, data preprocessing, model evaluation, hyperparameter tuning, model deployment, and monitoring.
  • At least one year of hands-on experience working on Generative AI or Large Language Model projects.
  • Strong understanding of Large Language Models and Natural Language Processing concepts.
  • Experience in prompt engineering and prompt optimisation, and designing and implementing Retrieval-Augmented Generation architectures.
  • Experience building agentic AI or multi-agent applications.
  • Practical experience with LangChain, LangGraph, OpenAI APIs, Hugging Face, and LangSmith.
  • Experience with vector databases and similarity-search technologies, including Pinecone and FAISS.
  • Knowledge of embedding models, chunking strategies, semantic search, document retrieval, and reranking.
  • Experience evaluating Retrieval-Augmented Generation solutions using metrics or frameworks such as RAGAS, BLEU, or ROUGE.
  • Hands-on experience with AWS services such as Amazon EC2, Amazon S3, Amazon SageMaker, and Amazon Bedrock.
  • Experience working with Docker, Git, JIRA, and CI/CD pipelines.
  • Candidates must have 4–6 years of overall professional experience.
  • Candidates must be immediate joiners.
  • Candidates should be based in Noida, Gurugram, Delhi, or another NCR location.
  • Candidates must be comfortable working in a hybrid model from the Gurugram office.
  • Candidates should be available for an interview on August 1 or August 3, 2026.

Responsibilities

  • Design, develop, test, and deploy scalable AI, machine-learning, deep-learning, and Generative AI solutions.
  • Build and optimise Retrieval-Augmented Generation pipelines using modern frameworks, embedding models, and vector databases.
  • Develop Large Language Model-powered applications using prompt engineering, AI agents, LangGraph, and multi-agent workflows.
  • Fine-tune, evaluate, deploy, and monitor machine-learning and deep-learning models.
  • Build REST APIs and backend services for AI applications using FastAPI or similar frameworks.
  • Design data-preprocessing, feature-engineering, model-training, and model-evaluation pipelines.
  • Integrate structured and unstructured data sources to deliver accurate and context-aware AI solutions.
  • Implement semantic search and document-retrieval architectures.
  • Evaluate Retrieval-Augmented Generation and Generative AI solutions using appropriate quality and performance metrics.
  • Collaborate with Data Engineering, DevOps, Product, and other cross-functional teams.
  • Ensure the scalability, reliability, security, and performance of AI applications in production environments.
  • Follow software-engineering best practices, coding standards, version-control processes, and Agile methodologies.
  • Troubleshoot model, API, data-pipeline, and production-performance issues.

Desired Qualifications

  • Experience deploying AI and Large Language Model applications in production environments.
  • Understanding of Large Language Model observability, hallucination control, guardrails, latency optimisation, and cost optimisation.
  • Experience integrating enterprise data sources with Generative AI applications.
  • Strong analytical, problem-solving, communication, and stakeholder-management skills.
  • A bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.

About the Company

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