As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.
Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Leadership Experience: At least 4 years of experience leading ML teams in Natural Language Processing (NLP) or Generative AI (GenAI) domains, with a proven ability to guide teams in achieving impactful results.
LLM Expertise: Advanced knowledge and experience in managing teams developing Large Language Models (LLMs), with strong expertise in the engineering aspects of scalable LLM deployment, ensuring optimal performance and minimal latency.
Academic and Applied Background:
MSc with 6+ years of professional experience, or PhD with 4+ years of experience, applying Machine Learning to solve business challenges.
Masters, PhD, or equivalent experience in a quantitative field (e.g., Computer Science, Engineering, Mathematics, Artificial Intelligence, Physics, etc.).
Strong advantage for candidates whose MSc or PhD thesis work is related to NLP, showcasing deep research capabilities in this field.
End-to-End R&D Proficiency: Demonstrated experience in designing and executing end-to-end research and development plans, from problem definition and data preparation
