OXMAN · 3 months ago
Machine Learning Research Engineer
New York, NY, US
Full-time
Hybrid
Mid, Senior Level
$75K/yr - $225K/yrOXMAN is a hybrid Design and R&D company that fuses design, technology, and biology to invent multi-scale products and environments. They are seeking a Research Engineer with expertise in Deep Reinforcement Learning, Deep Generative Modeling, and Data-Driven Design Optimization to develop innovative design methods that enhance ecological processes. The role involves creating approaches that integrate generative design, ecosystem simulation, and optimization techniques to improve ecosystem services.
Biomass EnergyBiotechnologyEnvironmental EngineeringManufacturing
Responsibilities
Develop and refine advanced deep generative models and reinforcement learning algorithms to generate, explore, and optimize built-environment design strategies aimed at enhancing ecosystem services
Create decision-making frameworks that combine procedural generation with machine learning and data-driven optimization, improving interactions between built and natural environments
Investigate and implement interfaces between procedural generation techniques, machine learning approaches, and deep generative modeling
Collaborate with computational ecologists to integrate generative design frameworks with ecosystem simulation models, producing architectural and infrastructural designs that interact positively with natural environments
Apply optimization and reinforcement learning techniques to align generative design outputs with ecological performance indicators, such as species richness, carbon sequestration, and water management
Collaborate with data scientists and ecologists to incorporate extensive, diverse datasets (remote sensing, climate data, biodiversity records) into generative and optimization methodologies
Contribute to model validation by comparing simulated results to empirical ecological data, ensuring accuracy and reliability
Prepare detailed technical documentation of methods, assumptions, and implementations to support reproducibility and knowledge sharing
Qualification
Required
Ph.D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or related fields
Proven experience developing and deploying deep generative models, reinforcement learning algorithms, and data-driven optimization methods in practical design problems
Strong knowledge in mathematical modeling, probabilistic methods, simulation techniques, procedural modeling, and complex systems
Proficiency in handling and analyzing large, heterogeneous datasets (environmental, climate, remote sensing) using Python, C++, or similar languages
Experience with GIS tools and remote sensing technologies for geospatial analysis
Demonstrated ability to work in cross-functional teams, bridging machine learning research with ecology, architecture, engineering, and design
Enthusiasm for pushing boundaries in design and science; ability to merge rigorous computational methods with innovative thinking
A commitment to Nature-centric principles and willingness to explore novel ways of integrating technology and ecology
Benefits
Variable compensation in the form of year-end bonuses
Benefits
Immigration assistance
Equity participation
Company
OXMAN
Oxman is a biotechnology company that combines design, technology, and biology from human-centric design to nature-centric design.
11-50 employees
H1B Sponsorship
OXMAN has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (1)
Funding
Current Stage
Early StageLeadership Team
Andrew Tom
Chief Financial Officer
Recent News
2024-01-09
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