Lead AI/ML Engineer About the Role

We are looking for an experienced Lead AI/ML Engineer to design, develop, and deploy AI and machine learning solutions at scale.

The role will focus on building production-ready Generative AI, LLM, and Machine Learning applications, while working closely with Product, Data, and Engineering teams. The ideal candidate should have strong hands-on expertise in AI/ML engineering, Python, LLMs, Agentic AI, and modern cloud-based AI platforms.

The role also involves technical leadership, mentoring, reviewing the work of other engineers, and communicating complex AI concepts and outcomes to senior stakeholders.

AI/ML Engineers develop and deploy software that enables machine learning models and AI algorithms to operate effectively in production environments.

The role involves working across areas such as Generative AI, Natural Language Processing (NLP), Natural Language Understanding (NLU), semantic understanding, intent classification, deep learning, computer vision, and speech technologies.

The candidate will work with large-scale computing frameworks and data platforms while applying knowledge of machine learning, statistics, probability, optimization, and experimental methodologies to develop practical AI solutions.

Primary Responsibilities AI Applications Feature Development

- Develop and refine LLM-based applications including chat, summarization, knowledge search, and data extraction.
- Apply prompt engineering techniques and support model fine-tuning and parameter-efficient tuning approaches such as LoRA.




- Design and implement RAG (Retrieval-Augmented Generation) workflows, including preprocessing, embedding generation, retrieval, and vector search.
- Develop AI-powered features that solve real-world business problems.

Model Architecture
- Work with transformer-based models and demonstrate a solid understanding of attention mechanisms, embeddings, and model behavior.
- Contribute to model interpretability, reliability, and performance improvements.
- Build, train, evaluate, and tune machine learning models as required.

AI Quality, Evaluation Responsible AI
- Improve model accuracy and reliability by reducing hallucinations through prompting, guardrails, and retrieval optimization.
- Develop and support benchmarking frameworks, evaluation tests, and AI quality checks.
- Contribute to responsible and reliable AI practices.
- Monitor model performance and identify opportunities for continuous improvement.

Integration AI Orchestration
- Build scalable services integrating AI APIs and models, including OpenAI, Azure AI, and open-source LLMs.
- Develop AI Agent and Multi-Agent workflows and orchestration frameworks.
- Work with vector databases such as FAISS, Pinecone, and pgvector.
- Integrate AI capabilities into enterprise applications and platforms.

Performance Optimization
- Improve AI application latency, throughput, scalability, and tok

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AIML (Human Capital or Corp. Governance) Professional (Bengaluru)
🏢 Mancer Consulting Services
📍 Bengaluru