- Lead the design and implementation of representation learning systems, embedding models, vector search solutions, and retrieval-augmented architectures.
- Define technical architecture for AI-first platforms utilizing foundation models, large language models, autonomous agents, and classical machine learning techniques.
- Establish best practices for agentic AI systems including orchestration, memory management, tool integration, confidence calibration, and human-in-the-loop workflows.
- Architect multimodal AI solutions that combine imagery, text, and structured data for detection, classification, reasoning, and decision support.
- Evaluate emerging AI technologies and guide adoption decisions across the organization.
- Translate complex business and technical challenges into scalable, explainable, responsible AI solutions.
- Define success metrics and partner with leadership to ensure measurable business impact.
- Mentor engineers and data scientists, helping elevate technical excellence across the team.
- Contribute to innovation through intellectual property development, research publications, and technical thought leadership.

Who you are
- 8+ years of relevant experience, including demonstrated hands on technical lead .
- Proven track record of leading the design and delivery of production ML systems end to end, and setting technical direction that other engineers build on.
- Deep expertise in representation learning and embeddings, vector similarity search, and retrieval-augmented approaches — able to architect the foundation-model core, not just contribute to it.
- Strong command of ML fundamentals, including regression, classification, forecasting,



and model interpretability.
- Hands-on experience with deep learning architectures such as CNN, LSTM, GRU, GANs, BERT, Diffusion Models, and Transformers.
- Substantial experience with LLMs (e.g., GPT-3/4, Claude, Mistral) and architecting agent-based solutions using frameworks like LangGraph, CrewAI, or AutoGen.
- Multimodal / vision-language model experience — jointly encoding imagery with text or structured data — at an architectural level.
- Proficiency in Python; familiarity with other programming languages like C++ or Java is a plus.
- Fluency with ML frameworks such as PyTorch, TensorFlow, scikit-learn, and experience working with large datasets and distributed systems.
- A track record of making independent architectural decisions, defending them with evidence, and holding a high measurement bar for whether systems actually work.
- Demonstrated ability to mentor senior engineers and lead cross-functional, agile teams.
- Excellent problem-solving and communication skills, including the ability to represent complex technical work to senior stakeholders.

We are looking for a Lead ML & AI Engineer to define and deliver the next generation of AI-powered platforms and intelligent automation solutions at CYIENT.

In this role, you will be positioned in customer workplace understand the requirement, translate into architecture & develop solution using machine learning, generative AI, agentic AI, multimodal systems, learning platforms. You will collaborate closely with engineering leaders, researchers, and product teams to architect scalable, production-ready AI solutions that solve complex, operational, and knowledge-driven challenges.

📌 Lead AI Engineer (Hyderabad)
🏢 Cyient
📍 Hyderabad