What success looks like in this role:
We are seeking an experienced Senior Machine Learning Engineer to join our team. In this role, you will be pivotal in advancing our in-house LLM-powered chatbot technologies through research, development, evaluation, and analytics. You will focus on tracking and experimenting with advancements in Retrieval-Augmented Generation (RAG) and its evaluation methodologies.
Key Responsibilities:
- Define Technological Vision: Develop and articulate the technological vision for our in-house chatbot evaluation & analytics engine, ensuring alignment with company goals and industry standards.
- Project Leadership: Collect requirements from in-house chatbot stakeholders including PMs, in-house chatbot core team, and ML team.
- Technological Leadership: Build core chatbot’s evaluation and continuous improvements systems components.
- Mentorship: Mentor and guide junior colleagues, fostering a culture of learning and development within the team.
- Research Engagement: Actively participate in bi-weekly machine learning paper review meetings, staying abreast of the latest developments and integrating relevant findings into our work.
- RAG Research Tracking: Actively track advancements in Retrieval-Augmented Generation (RAG), advanced RAG methodologies, and RAG evaluation research.
You will be successful in this role if you have:
- Experience: Minimum of 4 years of experience leading machine learning and or data engineering projects, demonstrating a track record of successful project delivery.
- LLM Implementation: Proven experience in implementing LLM-based solutions in production environments, with a deep understanding of the associated challenges and best practices.
- Proficiency in Python and its machine learning libraries (e.g., Pandas, scikit-learn).
- Experience with Spark or other distributed computation frameworks, enabling efficient processing of large datasets.
- RAG Expertise: Strong understanding and experience with Retrieval-Augmented Generation (RAG) techniques, including tracking and experimenting with the latest advancements.
- Mentorship: Demonstrated ability to mentor and develop other machine learning team members, sharing knowledge and expertise effectively.
- Algorithm and Data Structures: Strong knowledge of algorithms and data structures, with the ability to apply this knowledge to solve complex problems.
- Adaptability: Quick to grasp new technologies and concepts, staying ahead in a rapidly evolving field.
- Communication Skills: Excellent communication skills, both written and verbal, with the ability to convey complex technical concepts to diverse audiences in English.
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