Staff ML Engineer
Designer Fund is a venture capital firm that invests in early-stage tech companies using design to improve health, sustainability, or prosperity for people. It backs founding teams, particularly those with design backgrounds, across sectors like fintech, healthcare, climate tech, and developer tools.
About Designer Fund
Designer Fund is an early-stage venture capital firm that invests in tech companies leveraging design to drive positive outcomes in health, sustainability, and financial prosperity. Its portfolio spans a wide range of sectors including financial infrastructure (Stripe), preventative health (Omada), collaborative tools (Notion), developer tools (Netlify), product management (Linear), payroll and benefits (Gusto), design tools (Framer), and healthcare infrastructure (Commure), among dozens of other companies across fintech, climate tech, healthcare, EdTech, and AI. The firm also runs 'Designer Founders,' a community and platform highlighting designers who have gone on to found and lead companies, reflecting its focus on backing design-driven founders and design-centric startups from early stages through growth and acquisition.
Skills
About the Role
You will play a central role in shaping how millions of riders and drivers move through cities every day. You'll sit at the intersection of machine learning, optimization, and real-world operations, turning complex, multi-dimensional challenges into the real-time intelligence that powers a mass-scale automated dispatch system. You'll work on problems that are genuinely hard, at a scale that is genuinely rare, where the solutions you build have a direct and visible impact on the efficiency and reliability of transit networks around the world.
Requirements
- Advanced degree (M.Sc. or PhD) in Computer Science, Mathematics or a closely related field, with a strong background in Machine Learning
- 8+ years of industry experience shipping machine learning models at production scale
- Deep, hands-on expertise in Machine Learning, with significant experience in reinforcement learning for complex, dynamic or constrained systems
- Excellent coding skills in Python or similar
- Strong applied research mindset able to translate ambiguous business/operational challenges into tractable ML formulations
- Strong communication skills and collaborative mindset
Responsibilities
- Own the development of ML models and optimization algorithms that drive real-time dispatch decisions across thousands of simultaneous rides, drivers, and operational constraints
- Design and implement online algorithms for real-time decision-making, balancing system utilization with high quality of service
- Model and mathematically represent competing demands on the system, translating operational complexity into tractable formulations
- Use statistical methods to analyse demand patterns, traffic dynamics, and fleet performance to inform algorithm development and strategy
- Collaborate with engineering, product, and operations teams to bring algorithmic work from research and prototyping through to production deployment and iteration
Benefits
- Health insurance with a discount for family members
- Hybrid work and an office in the heart of TLV, close to the light rail and train station
- Freefit and other sports lessons
- 10bis/Cibus subsidy
- Happy hours, team events, and communities