About the Role
We are seeking a highly skilled and experienced Lead Machine Learning Engineer to join our team. As a key member of our engineering organization, you will be responsible for shaping the technical roadmap and contributing to the implementation of best practices in machine learning.
Key Responsibilities
* Define architectural patterns for scalable LLM pipelines, ensuring robust versioning, monitoring, and adherence to best practices.
* Drive the integration of external knowledge bases and retrieval systems to augment LLM capabilities.
* Effective RAG architectures and technologies for organizing complex domain-specific data (e.g. vector databases, knowledge graphs) and effective knowledge extraction.
* Explore and benchmark state-of-the-art LLMs, tuning, adaptation, and training for performance and cost efficiency.
* Incorporate recent trends like instruction tuning, RLHF, or LoRA fine-tuning for domain customization.
* Embed domain-specific ontologies, taxonomies, and style guides into NLP workflows to adapt models to unique business contexts.
Requirements
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
* Minimum 5 years of experience implementing machine learning projects.
* At least 2 years in a senior or lead role.
* Demonstrated expertise integrating modern LLMs into production systems.
* Strong leadership skills, including proven experience driving technical projects to successful completion in agile environments.
* Strong communication skills to align technical solutions with business goals.
* Ability to mentor and foster innovation within the team.
* Experience with Retrieval-Augmented Generation (RAG) architectures and integrating with vector and graph databases.
* Experience with Transformer-based LLMs (e.g. GPT-4, Claude, Gemini, Llama, Falcon, Mistral).
* Demonstrated ability to fine-tune and optimize LLMs for quality, latency, sustainability, and cost-effective performance.
What We Offer
A dynamic and supportive work environment that fosters collaboration, growth, and innovation.
Opportunities for professional development and career advancement.
A competitive compensation package.
A comprehensive benefits program.
A chance to work on cutting-edge technology and make a meaningful impact.
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