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AI/ML Engineer – Agentic Systems ( 3 to 8 yrs )
AI/ML Engineer – Agentic Systems ( 3 to 8 yrs )AIMLEAP • Delhi, IN
AI / ML Engineer – Agentic Systems ( 3 to 8 yrs )

AI / ML Engineer – Agentic Systems ( 3 to 8 yrs )

AIMLEAP • Delhi, IN
4 days ago
Job description

AI / ML Engineer – Agentic Systems

Experience : 3–8 Years

Location : Remote

Mode of Engagement : Full-time

No. of Positions : 4

Educational Qualifications : B.E. / B.Tech / M.E. / M.Tech in Computer Science, AI / ML, Data Science, or related field

Industry : IT – AI / ML Services

Notice Period : Immediate

What We Are Looking For

  • 3–8 years of hands-on experience in AI / ML with strong practical exposure to Transformer-based models .
  • Proven experience in fine-tuning, optimizing, and deploying LLMs (BERT, T5, GPT-style, LLaMA, Mistral, etc.).
  • Strong Python skills for model training, inference pipelines, APIs, and system integration.
  • Real-world experience working with agentic / multi-agent AI systems (planner–executor, supervisor–worker patterns, tool-using agents).
  • Ability to independently own model development → experimentation → production deployment .
  • Experience handling latency, cost, scalability, and monitoring in production AI systems.

Responsibilities

  • Design, fine-tune, and deploy Transformer-based models for NLP, reasoning, information extraction, and generation tasks.
  • Build and manage multi-agent AI systems for task decomposition, orchestration, and decision-making.
  • Implement efficient inference pipelines with batching, caching, quantization, and latency optimization.
  • Develop production-grade REST APIs using FastAPI / Flask and containerize services using Docker.
  • Collaborate with internal teams and clients to convert business requirements into scalable AI solutions.
  • Monitor model performance, accuracy, drift, and cost; continuously improve system reliability.
  • Stay up to date with advancements in transformer architectures, LLMs, and agent-based AI systems .
  • Qualifications

  • Bachelor’s or Master’s degree in Computer Science, AI / ML, or a related discipline.
  • Minimum 3 years of hands-on experience with Transformer architectures.
  • Strong working experience with Hugging Face Transformers and PyTorch (preferred) or TensorFlow / JAX.
  • Solid understanding of attention mechanisms, encoder–decoder models, embeddings, and fine-tuning strategies .
  • Familiarity with multi-agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, or similar).
  • Experience with REST APIs, Docker, Git , and cloud deployment on AWS or GCP .
  • Strong communication skills with the ability to explain complex AI concepts to non-technical stakeholders.
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