Machine Learning Engineer
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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 domain—allowing 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 interrelations—not isolated objects—that 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 systems—from single-celled organisms to whole ecologies and even biotic-abiotic hybrid systems.
Core responsibilities
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.
PI250969642
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 domain—allowing 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 interrelations—not isolated objects—that 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 systems—from single-celled organisms to whole ecologies and even biotic-abiotic hybrid systems.
Core responsibilities
- Apply techniques from artificial intelligence and machine learning to research, develop, implement, and evaluate state-of-the-art algorithms for applications related to design, fabrication and biology
- Research and develop methods and frameworks in the area of multi modal machine learning, deep generative modelling and deep reinforcement learning to support OXMANs vision of integrated physical, digital and biological systems
- Perform and conduct data gathering and data analysis on environmental and biological data as it relates to OXMANs design goals.
- Actively seek opportunities to publish work in top-tier journals and other platforms for promoting scientific knowledge
- Nurture and augment the scientific vision of OXMAN, upholding core design principles and ensuring the highest and most innovative quality of work
- Actively partner with a multidisciplinary team of professionals, including other biologists, engineers, and designers, across scientific and design pursuits
- Communicate ideas, work, and progress clearly, including by engaging in team meetings, presentations, and other creative communication outlets
- PhD or equivalent, with a focus on computer science, artificial intelligence, machine learning, applied data science, bioinformatics, mathematics, physics, or relevant field
- Minimum 4 years of experience with machine learning
- Experience in one or more of the following: Multi Modal Machine Learning, Deep Generative Modeling, Deep Reinforcement Learning.
- Portfolio demonstrating out-of-the-box thinking and integration of artificial intelligence methods to other domains.
- Fluency with programming (e.g., Python, C++, ...)
- Expert knowledge in Machine Learning Frameworks (Pytorch, JAX, ...)
- Ability to thrive in a fast-paced entrepreneurial environment
- Excellent independence, self-motivation, organizational skills, and attention to detail
- An interest in design, biology, architecture, artificial intelligence, and/or sustainability is a plus
- Strong commitment to the team; maintains positive working relationships with diverse people, including internal team and external partners
- Embodies ethics and integrity in all work, respecting both company and broader community policies in all conduct
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.
PI250969642
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