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.