AI Ml Engineer

Senior AI/ML Engineer

Key Responsibilities;

• Design, develop, and deploy AI/ML models with a strong emphasis on applied problem-solving.
  
• Work on

  Generative AI, LLMs, RAG pipelines, and prompt engineering

  to build next-gen AI solutions.
• Implement

  MLOps automation

  for end-to-end model lifecycle management using tools like MLflow, Kubeflow, or SageMaker.
• Optimize training and inference workflows leveraging

  NVIDIA GPU tools

  (CUDA, TensorRT, Triton Inference Server).
• Collaborate with cross-functional teams to design

  real-time AI pipelines and scalable deployment architectures

  .
• Stay ahead of industry trends, research advancements, and best practices in AI/ML and Generative AI.
  

Must-Have Skills (5+ Years Relevant Experience)

• Strong applied expertise in

  Artificial Intelligence & Machine Learning

  .
• Proven experience in

  Generative AI & LLMs

  fine-tuning, retrieval-augmented generation (RAG), and prompt engineering.

• MLOps proficiency

  automation of model training, deployment, and monitoring using MLflow, Kubeflow, SageMaker, or similar tools.

• Python – Expert level

  , with hands-on experience in PyTorch, TensorFlow, Hugging Face, Scikit-learn, etc.
• Experience with

  NVIDIA GPU frameworks and tools

  – CUDA, TensorRT, Triton Inference Server.
• Strong knowledge of

  model deployment, serving, and real-time AI pipelines

  .

Good to Have

• Experience with

  JavaScript/TypeScript

  for AI/ML integration with front-end systems.
• Familiarity with modern AI/ML tools: LangChain, LlamaIndex, Vector Databases (FAISS, Pinecone, Weaviate).
  
• Cloud ML platforms –

  AWS, GCP, Azure ML

  .
• Knowledge of

  Docker, Kubernetes, and RESTful APIs

  for containerized deployments.

Eligibility

• Minimum

  5+ years of relevant, hands-on AI/ML/LLM experience

  (not just research, but applied/production).
• Willingness to

  work from Hyderabad

  (relocation required if not currently based in Hyderabad).
• Passionate about building

  impactful, production-grade AI systems

  that scale.