Algorithm Engineer

About

A design-tech start-up from Harvard charting a radical new standard: to eliminate material waste with great design and bleeding-edge AI. Our design has won the Global Change Award considered the “Nobel Prize of Fashion” while our technology has won MIT Solve’s Global Challenge.

Our dynamic team includes award-winning leaders from Instagram to Adidas, passionately committed to zero waste, obsessed with proving the impossible possible.

Key Responsibilities

• Develop, refine, and maintain optimization algorithms in C++ using linear algebra techniques to support zero waste design outputs.
• Explore and implement multivariate optimization methods—from simplex to gradient-based and evolutionary algorithms— tuning for performance and robustness in production.
• Design and optimize custom cost functions for machine learning models, including hyperparameter tuning and loss shaping to improve practical outputs.
• Boost computational performance through algorithmic redesign, greedy heuristics, parallelization, and profiling at a low system level.
• Write modular, scalable, and clean code across C++, Python and at least one additional systems language (e.g., Rust or JavaScript).
• Analyze the time and space complexity of algorithms and systems, ensuring efficient performance at scale.
• Build and use internal debugging tools, visualizers, and test harnesses to speed up experimentation and improve engineering workflows.
• Collaborate with front-end engineers, 2D/3D designers, and researchers to integrate algorithmic solutions seamlessly into user-facing product features.
• Translate academic and theoretical breakthroughs into real- world, scalable solutions adopted by leading fashion and automotive partners

Qualifications

• Have experience implementing, improving, and maintaining optimization algorithms in C++ using linear algebra techniques (e.g., vector and matrix manipulation).
• Are comfortable with multivariate optimization methods—from classic simplex-style solvers to modern gradient-based and evolutionary approaches—and have a track record of tuning them for speed and robustness.
• Have hands-on work experience with machine-learning algorithms that minimize or otherwise optimize cost functions, including custom loss design and hyper-parameter search.
• Are good at communicating the ins and outs of thorny technical problems in simple language, allowing team members to zero in on and demolish issues and bugs.
• Are skilled in boosting ML/optimization performance through algorithmic redesign, greedy heuristics, parallelization, and low- level profiling.
• Are familiar with object-oriented and functional programming paradigms, together with rigorous analysis of time and space complexity to keep web-scale pipelines snappy.
• Are proficient in C++ and Python, and at least one additional systems language (e.g., Rust or JavaScript for WebAssembly) for bridging core solvers to the product front end.
• Are comfortable dogfooding internal tools—building quick-turn scripts, debuggers, visualizers, and test harnesses that shorten feedback loops for yourself and the wider team.
• Are collaborative and excited to partner with designers, front-end engineers, and researchers to translate algorithm innovation into intuitive features to drive a zero waste mission.
• Are energized by turning cutting-edge research into scalable, user-ready tools, and love solving hard, technical problems that have meaningful, real-world impact

Why We May NOT Be For You

• We’re working on bleeding-edge technology and breaking new ground, which also means a lot of uncertainty and constant change/re-prioritization.
• We’re a small team without many of the amenities, infrastructure, and proven practices you may be used to from working with larger, established teams.

Why Us?

• From turning the largest music record labels’ tour merchandise zero waste to creating the first zero waste car components, you will be making outsized impact daily.
• You will get to work with the best of the best through our global team, from a world-renowned AI professor from Tokyo, to Levi’s former head of technical design from Paris.
• We know that we are changing the game in design. We have proven 10x more impact in material saving, environmental benefits, and material cost saving than any other solution today.
• -Without a sales or marketing team, we have attracted the most iconic global brands across apparel and automotive industries.