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

AI/ML Engineer – Transformers & Multi‑Agent Systems

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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.