Lead Machine Learning Engineer

Ramboll Tech is seeking a Lead Machine Learning Engineer in Chennai, Tamil Nadu, to spearhead the creation of cutting-edge AI solutions. This role involves technological leadership, driving innovation in LLM pipelines, and integrating external knowledge bases. You will research and develop RAG architectures, explore state-of-the-art LLMs, and optimize models for performance and cost efficiency. Responsibilities include defining architectural patterns for scalable LLM pipelines, implementing RAG architectures with vector databases and knowledge graphs, and tuning LLMs using techniques like instruction tuning and RLHF. You will also analyze model quality, latency, and sustainability metrics, define and own ML-Ops for your pod, and develop experiments for continuous improvement. Establishing scalable coding standards and best practices for production-ready systems is crucial. Additionally, you will mentor other ML engineers, fostering a culture of collaboration and growth.

As a sparring partner for product owners and the Chapter lead, you will shape the technical roadmap and contribute to best practices within your product team and the global ML Engineering Chapter. You will work with global leads, subject matter experts, and other ML Engineers to deliver impactful AI solutions.

Key Responsibilities:

• Define and implement scalable LLM pipeline architectures with robust versioning and monitoring.
• Integrate external knowledge bases and retrieval systems to enhance LLM capabilities.
• Develop and optimize Retrieval-Augmented Generation (RAG) architectures, including vector databases and knowledge graphs.
• Explore, benchmark, and tune state-of-the-art LLMs for performance and cost efficiency.
• Incorporate advanced LLM techniques such as instruction tuning, RLHF, and LoRA fine-tuning.
• Embed domain-specific ontologies and taxonomies into NLP workflows.
• Analyze and optimize models for quality, latency, sustainability, and cost.
• Define and manage ML-Ops for your product team.
• Develop experiments for ongoing model evaluation and improvement.
• Establish and maintain scalable coding standards and best practices.
• Mentor and support the growth of other ML engineers.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Minimum 5 years of experience in machine learning project implementation.
• At least 2 years in a senior or lead role.
• Demonstrated expertise integrating modern LLMs into production systems.
• Proven leadership in driving technical projects in agile environments.
• Strong communication skills to align technical solutions with business goals.
• Ability to mentor and foster innovation.
• Expertise in building Retrieval-Augmented Generation (RAG) architectures and integrating with vector and graph databases.
• In-depth experience with Transformer-based LLMs (e.g., GPT-4, Claude, Gemini, Llama, Falcon, Mistral).
• Experience in fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost.
• Advanced Python proficiency and expertise with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain.
• Experience with MLOps tools (e.g., Docker, Kubernetes, Azure ML Studio, MLFlow).
• Hands-on experience with cloud environments (preferably Azure) for AI deployment.
• Familiarity with document processing and knowledge extraction tools.
• Experience with relational (SQL) and NoSQL databases.
• Familiarity with data platforms like Snowflake or Databricks.