AI ML Developer - Hyderabad Indore - Job ID 128632

We are looking for a passionate and skilled AI/ML Engineer with 2–4 years of experience to design, develop, deploy, and operate machine learning and Generative AI solutions in real production environments. You will work closely with data scientists, backend engineers, and product teams to integrate AI-driven capabilities into scalable and reliable systems.

Key Responsibilities

• Design, develop, deploy, and maintain machine learning and deep learning models for real-world, production use cases.
• Work with Python-based frameworks such as TensorFlow, PyTorch, and Scikit-learn to build and optimize models.
• Perform data preprocessing, feature engineering, model training, and hyper-parameter tuning.
• Fine-tune and train Large Language Models (LLMs) for domain-specific use cases, including prompt engineering, fine-tuning pipelines, and evaluation.
• Research, experiment, and build solutions using LLMs, embeddings, NLP, and generative AI tools such as OpenAI, LangChain, and Hugging Face.
• Collaborate with backend and platform teams to integrate models into production systems (APIs, microservices, and data pipelines).
• Build and manage ETL pipelines, handle large datasets, and ensure data quality and consistency.
• Own and track ML and business metrics (for example: model accuracy, latency, precision/recall, drift, cost, and business impact KPIs) and continuously improve them.
• Work on production-grade AI systems, including monitoring, logging, alerting, and incident handling.
• Ensure model service uptime, availability, and reliability in line with defined SLAs/SLOs.
• Optimize model performance, scalability, and inference efficiency for real-time and batch workloads.
• Partner with product and stakeholders to clearly define problem statements, success metrics, and acceptance criteria.
• Stay up to date with the latest advancements in AI, ML, and GenAI technologies.
  
  

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
• Solid understanding of machine learning algorithms, data preprocessing techniques, and model evaluation strategies.
• Hands-on production experience deploying and operating ML/LLM systems (not only experimentation or notebooks).
• Experience in NLP, LLM, or Generative AI projects is highly desirable.
• Experience with LLM fine-tuning, training workflows, and evaluation frameworks.
• Familiarity with cloud environments such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure for ML deployment.
• Experience with version control (Git) and CI/CD pipelines.
• Strong understanding of API development using FastAPI or Flask for serving ML models.
• Knowledge of MLOps and model lifecycle tools such as MLflow, Kubeflow, or Airflow.
• Exposure to vector databases such as Pinecone, ChromaDB, or Weaviate.
• Ability to define, monitor, and improve model and platform metrics (accuracy, latency, throughput, drift, and cost).
• Understanding of reliability, uptime, monitoring, and operational best practices for ML services.
• Prior experience working on AI-powered SaaS products or intelligent automation systems.
• Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.