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๐ค Closed by robot after apply link errored w/ code 404 2 years ago
About Paperspace\n\nPaperspace builds tools and infrastructure to make accelerated computing simple and accessible.\n\nPaperspace is backed by leading investors including Y Combinator, Initialized Capital, Battery Ventures, and Intel Capital.\n\nThe Roleย \n\nWe are looking for a Growth ML Engineer to cultivate a global, diverse community of developers and machine learning engineers. Youโll work at the intersection of marketing, sales, and customer support to showcase the value of the Gradient platform to aspiring and veteran ML developers. You'll help drive adoption, understand innovative customer use cases, and serve as the primary problem solver in our customers' ML workflows.ย \n\nIn this role, you'll be working directly with customers on applied ML problems across a range of use cases such as computer vision, robotics, natural language processing, and more. You'll have the opportunity to collaborate with ML teams across several industries to improve their workflow and educate them on ML best practices.\n\nThis is a perfect opportunity for anyone who has machine learning experience, is customer-oriented, and is looking to work with the top ML companies in the world. If you enjoy working with highly technical engineering teams and thrive in an autonomous environment, we encourage you to apply.ย \n\nWhat you'll be doingย \n\nโข Deliver high-level, detailed technical presentations and demos tailored to customersโ requirements alongside the Head of Sales and/or Sales Development Representative\nโข Provide product support and assist prospects, customers, and partners with their technical issues\nโข Architect and prototype solutions for customers\nโข As a technical first responder to prospective and enterprise customers, assist in the diagnosis of technical issues/bugs and work with our Support and Engineering teams to resolve more advanced issues when necessary\nโข Effectively communicate client needs to the engineering team for future product enhancements\nโข Design and build clear and compelling example projects to guide users and showcase our product to customers: end-to-end ML models with reproducible workflows, illustrative tutorials, and how-tos for specific tasks in Gradient, general explanatory blog posts, etc\nโข Listen to and partner with our customers, academic users, and the broader community to understand and help prioritize their workflows in Gradient\nโข Keep the organization apprised of new developments in applied & theoretical MLย \n\nWhat we're looking forย \n\nโข 3+ years of experience in a professional working environment in an ML Engineer or adjacent role\nโข Experience using one or more of the following packages: TensorFlow/Keras, PyTorch\nโข Strong programming proficiency in Python and eagerness to help customers who are primarily users of ML/DL frameworks and tools be successful\nโข Excellent communication and presentation skills, both written and verbal\nโข Ability to effectively manage multiple conflicting priorities, respond promptly, and manage time effectively in a fast-paced, dynamic team environment\nโข Ability to break down complex problems and resolve them through customer consultation and execution.\nโข Experience with cloud platforms (AWS, GCP, Azure)\nโข Experience with Linux/Unix\nโข Applied machine learning experience in the industry: training, tuning, debugging, and deploying machine learning models integral to a product or service, in a collaborative team environment\nโข Familiarity with a range of ML frameworks and domains (computer vision, natural language processing, reinforcement learning, statistics, etc)\nโข Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledgeย \n\nStrong Plus\nย \nโข Proficiency with one or more of the following packages: TensorFlow/Keras, PyTorch, HuggingFace, Fastai, scikit-learn, XGBoost, Jupyter\nโข Experience with hyperparameter optimization solutions\nโข Experience with data engineering, MLOps, and tools such as Docker and Kubernetes\nโข Experience with data pipeline tools\nโข Experience as an ML educator and/or building and executing customer training sessions, product demos, and/or workshops at a SaaS company\nโข You have thought deeply about your role in the future of artificial intelligence/technological advancement and want to help make machine learning more accessible, transparent, and collaborative\n\nOur Teamย \n\nPaperspace values technical excellence in an open and inclusive environment. The team is primarily based in NYC, but we have a strong remote/hybrid team. Communication is paramount and mutual respect is at the core of our collaborative work environment.ย We are also committed to building a team that represents a variety of backgrounds, perspectives, and skills. We believe creating a more diverse team directly impacts our ability to collaborate effectively, build a better community, and produce better products.\n\nBenefits\n\nโข Multiple health care insurance options with premium plans in addition to vision and dental insurance plans\nโข 401(k) Plan with employer matching\nโข Commuter benefits with a contribution from the company \nโข Responsible Time Off Policy \nโข Generous and flexible parental leave\nโข Fitness & wellness benefit\nโข Remote friendly and hybrid office environment for New York team members\n\nWe are an equal opportunity employer that values and welcomes diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.\n\n#LI-Remote \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Marketing, Engineer, Social Media, Executive, Cloud, Python, Sales and SaaS jobs that are similar:\n\n
$70,000 — $115,000/year\n
\n\n#Benefits\n
๐ฐ 401(k)\n\n๐ Distributed team\n\nโฐ Async\n\n๐ค Vision insurance\n\n๐ฆท Dental insurance\n\n๐ Medical insurance\n\n๐ Unlimited vacation\n\n๐ Paid time off\n\n๐ 4 day workweek\n\n๐ฐ 401k matching\n\n๐ Company retreats\n\n๐ฌ Coworking budget\n\n๐ Learning budget\n\n๐ช Free gym membership\n\n๐ง Mental wellness budget\n\n๐ฅ Home office budget\n\n๐ฅง Pay in crypto\n\n๐ฅธ Pseudonymous\n\n๐ฐ Profit sharing\n\n๐ฐ Equity compensation\n\nโฌ๏ธ No whiteboard interview\n\n๐ No monitoring system\n\n๐ซ No politics at work\n\n๐
We hire old (and young)\n\n
\n\n#Location\nUnited States