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AI/ML Engineer – Multi‑Agent Systems (2 to 12 yrs)
AI/ML Engineer – Multi‑Agent Systems (2 to 12 yrs)AIMLEAP • Delhi, IN
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AI / ML Engineer – Multi‑Agent Systems (2 to 12 yrs)

AI / ML Engineer – Multi‑Agent Systems (2 to 12 yrs)

AIMLEAP • Delhi, IN
6 days ago
Job description

AI / ML Engineer – Transformers & Multi‑Agent Systems

Experience : 2–12 Years

Location : Remote

Mode of Engagement : Full-time

No. of Positions : 4

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

Industry : IT – AI / ML Services

Notice Period : Immediate Joiner

What We Are Looking For :

  • 2–12 years of experience in AI / ML with strong hands-on expertise in Transformer-based models.
  • Proven experience fine-tuning, optimizing, and deploying large transformer models.
  • Strong Python skills for model training, inference pipelines, APIs, and system integration.
  • Experience working with multi-agent or collaborative AI systems (planner–executor, supervisor–worker patterns).
  • Ability to independently own model development, experimentation, and production deployment.

Responsibilities :

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

  • Bachelor’s or Master’s degree in Computer Science, AI / ML, or a related discipline.
  • 2+ years of experience working with Transformer architectures and deep learning systems.
  • Hands-on experience with Hugging Face Transformers, PyTorch, TensorFlow, or JAX.
  • Experience with attention mechanisms, encoder–decoder models, fine-tuning strategies, and embeddings.
  • Familiarity with multi-agent frameworks, task planners, evaluators, and feedback loops.
  • Experience with REST APIs, Docker, Git, and cloud deployment (AWS / GCP).
  • Strong communication skills and ability to explain complex AI concepts to non-technical stakeholders.
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    System Engineer • Delhi, IN

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