Senior ML Software Engineer

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. 

- 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.