OXMAN
OXMAN is a hybrid Design and R&D company that fuses design, technology, and biology to invent multi-scale products and environments. The fusion of disciplines within our work opens previously impossible opportunities within each domainβallowing design to inspire science and science to inspire design.
At OXMAN, we question dominant modes of design that have divorced us from Nature by prioritizing humanity above all else (human-centric design). Although it is design that has caused this rift, we believe that design also offers the greatest opportunity to heal it.
We propose a Nature-centric approach that delivers design solutions by, for, and with the natural world, while advancing humanity. In this pursuit, we reject all forms of segregation and instead call for a radical synergy between human-made and Nature-grown environments.
This approach demands that we design across scales for systems-level impact. We consider every designed construct a whole system of heterogeneous and complex interrelationsβnot isolated objectsβthat are intrinsically connected to their environments. In doing so, we open ourselves up to moving beyond the mere maintenance toward the advancement of Nature.
Summary
OXMAN is seeking a Machine Learning Engineer to join an all-star interdisciplinary team of deep thinkers and brilliant makers, with the aim to leverage artificial learning systems as a tool for mediation between human-made and nature-grown environments. By employing a generative approach and a commitment to process-oriented creation at OXMAN, the Machine Learning Engineer will play a crucial role in a variety of endeavors. These range from design tasks to technological platform advancement, all with the overarching objective to facilitate mediation and dialog and opening opportunities for interactions of combined systems that unite physical, digital, and biological realms.
In this position they will design, optimize, and deploy machine learning pipelines using large multimodal datasets containing heterogeneous and complex information related to biology, design, and sustainability. Lead the development of deep generative modeling efforts to explore design spaces and develop real-world deep reinforcement learning methods in biological-artificial hybrid systems. Successful applicants embody stellar technical skills, hold the capacity to navigate and resolve uncertainty, and demonstrate a unique ability to find synergies between biology (wetware), computing (software) and fabrication (hardware). The Machine Learning Engineer will play a key role in researching and developing novel algorithms, models, and methods for solving unique challenges within a variety of biological and bio-inspired systemsβfrom single-celled organisms to whole ecologies and even biotic-abiotic hybrid systems.
OXMAN does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, or any other legally protected characteristics.
NYC Salary Range: $83,000-$225,000
Salary is based on a number of factors including job-related knowledge, skills, experience, and other business and organizational needs. Our compensation package also includes variable compensation in the form of year-end bonuses, benefits, immigration assistance, and equity participation.