Team Lead Algorithm Engineering

Fetcherr experts in deep learning, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We are seeking a Team Leader to lead and mentor a team of engineers and data scientists. You’ll guide the team building end to end features as part of our pricing and market forecasting systems, shaping how AI transforms the aviation industry and beyond. This role blends leadership with technical expertise to drive the development of innovative and scalable algorithmic solutions.

Key Responsibilities

• Lead and mentor a multidisciplinary team of engineers and data scientists – setting goals, coaching, and growing careers
• Own the roadmap for algorithmic development, balancing long-term innovation with short-term business needs
• Drive cross-functional collaboration with Product, Engineering, and Business stakeholders to ensure alignment and delivery
• Shape team culture – foster technical excellence, psychological safety, continuous learning, and accountability
• Represent the team to leadership and external stakeholders, communicating progress, risks, and impact
• Provide hands-on technical guidance in algorithms, optimization, and large-scale data processing
• Review designs, prototypes, and code to ensure robustness, scalability, and performance
• Stay engaged with research and industry trends to keep algorithms state-of-the-art
  
  

• 5+ years of experience in production algorithm or machine learning development, with 2+ years in a leadership role
• Proven ability to manage and grow agile cross-functional teams delivering impactful solutions
• Strong background in data structures, algorithms, and computational complexity
• Proficiency in Python and libraries such as NumPy, SciPy, and Pandas
• Solid software engineering practices: code reviews, testing, and version control
• Excellent communication skills to bridge between technical and non-technical stakeholders
• Goal and KPI driven approach for managing teams
  
  

• Experience with mathematical optimization (linear programming, convex optimization)
• Exposure to MLOps and cloud infrastructure (Docker, Kubernetes, Airflow)
• Background in pricing, revenue management, or demand forecasting