Machine Learning Engineer - Remote, Contract or Full Time at Imbue (formerly Generally Intelligent) #vacancy #remote

[Contract] Machine Learning Engineer – Remote, Contract or Full Time at Imbue (formerly Generally Intelligent) (United States) | BEAMSTART Jobs Machine Learning Engineer – Remote, Contract or Full Time Imbue (formerly Generally Intelligent) United States Date Posted 09 Jan, 2024 Work Location San Francisco, United States Salary Offered $80000 — $300000 yearly Job Type Contract Experience Required No experience required Remote Work Yes Stock Options No Vacancies 1 available As a remote software engineer, you’ll work very closely with a senior member of our research team on cutting-edge deep learning infrastructure and tooling towards the goal of creating general human-like machine intelligence. We’re looking for someone who’s super excited to build tools (ex: experiment tracking tools, model debugging methods, automated hyperparameter optimizers, developer tooling, etc). If interested, apply here or on Work at a Startup! Example projects Implement a self-supervised network using contrastive and reconstruction losses. Create a library on top of PyTorch to enable efficient network architecture search. Open source internal tools. Implement networks from newly published papers. Work on tools for simple distributed parallel training of deep neural networks. Develop more realistic simulations for training our agents. Design automated methods and tools to prevent common issues with neural network training (e.g. overfitting, vanishing gradients, dead ReLUs, etc). Create visualizations to help us deeply understand what our networks learn and why. You are Very comfortable writing Python. Excited to work on open source code. Passionate about engineering best practices. Self-directed and independent. Excellent at getting things done. [Bonus] Familiar with PyTorch and training deep neural networks. Benefits Work directly on creating software with human-like intelligence Very generous compensation Flexible working hours Work remotely with a team that understands remote work Focus on coding and nothing else: no expectation that you attend standup, spend time doing sprint planning, etc. Work with other great programmers who care about their craft. e.g: we have deterministic formatting, zero linter errors, wide type coverage with MyPy, and even our deep learning code has tests. About us Imbue builds AI systems that reason and code, enabling AI agents to accomplish larger goals and safely work in the real world. We train our own foundation models optimized for reasoning and prototype agents on top of these models. By using these agents extensively, we gain insights into improving both the capabilities of the underlying models and the interaction design for agents. We aim to rekindle the dream of the personal computer, where computers become truly intelligent tools that empower us, giving us freedom, dignity, and agency to pursue the things we love. About Imbue (formerly Generally Intelligent) Company Size: 11 – 50 People Year Founded: 2021 Country: United States Company Status: Actively Hiring Looking for Partners Looking for Clients Raising Funds Share This Job More Contract Jobs Formulation Scientist Gurugram, India Contract More Companies Hiring Decohere United States SnapTrade Canada Novel United States Playground United States Langdock United States BEAMSTART brings you the latest news, databases, and jobs from all around the world on startups, technology, and business. Stay updated with industry news, plug-in to exciting community events, and discover incredible career opportunities with the world’s most innovative companies. Discover Jobs Full Time Part Time Contract Internship Volunteer Companies Candidates Post a Job For Recruiters Our Company News Jobs Database About Us Download App More © Copyright 2024 BEAMSTART . All Rights Reserved. #J-18808-Ljbffr

remote work deep-learning mypy Artificial intelligence (AI) Python visualization Machine Learning neural-network open-source Software Development Engineer simulation PyTorch

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