Machine Learning Engineer
March 16
🏢 In-office - Manhattan
Description
• 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. • The Machine Learning Engineer will play a crucial role in a variety of endeavors ranging from design tasks to technological platform advancement with the overarching objective to facilitate mediation and dialog and opening opportunities for interactions of combined systems that unite physical, digital, and biological realms. • 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.
Requirements
• 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
Benefits
• 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.
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