\nMatterport seeks an enthusiastic Sr. Manager of ML Production Engineer to join our Vision & Learning team. You’ll be responsible for leading and managing the ML Production Engineering function and engineering team responsible for Matterport’s 3D reconstruction pipeline. The ideal candidate is an individual who thrives in dynamic environments orchestrating high talent engineers to optimize ML Ops and Dev Ops for new and existing capabilities. You will collaborate with machine learning engineers and data scientists to design and implement efficient and scalable machine learning pipelines, monitoring and testing frameworks, and data management processes. You will work with software engineers to ensure the seamless integration of machine learning models into our applications and services.  This position will report to the Software Vice President for Vision & Learning.   \n\n\n\nWhat you will do:\n* Bring technical experience & leadership to critical systems including Cloud Architecture, Machine Learning Operations, back-end Software Engineering, and Distributed Systems.\n* Work cross-functionally to establish product definition and design as new capabilities are brought from development into production.\n* Lead and manage cross-functional engineering projects with multiple stakeholders, with regular reporting to executive stakeholders.\n* Lead by example as a working manager with strong hands-on engineering fundamentals.\n* Work closely with internal and contracted data providers in development of dataset for training production networks as well as development networks.\n* Lead and manage senior engineers empathically; maximizing high talent individuals in dynamic product environments.\n* Work with cross-functional teams across Product, Sales, Customer Success and Business Development\n* Advocate for new technical architecture and innovation \n* Implement and refine development and cross-functional processes\n* Hire, mentor, lead, and coach senior and principal engineers to meet their full potential\n* Act as a leader for implementing best-practices across the organization\n\n\n\n Who you bring:\n* Master’s degree in Computer Science, Electrical Engineering, or related field, or equivalent experience.\n* 5-8+ years of experience in software engineering, Dev Ops & ML Ops, or related fields.\n* Strong proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, MMdetection, Detectron and, Pytorch Lightning.\n* Strong knowledge of machine learning pipelines and workflows for training, validation, and deployment of models, e.g. Experience with containerization and orchestration tools such as Docker, Kubernetes, Kubeflow, MLFlow.\n* Strong experience with AWS cloud services\n* Strong knowledge of data management processes for large-scale machine learning datasets.\n* Experience with DevOps and Infrastructure as Code (IaC) tools such as Terraform, Ansible, or CloudFormation.\n* Strong knowledge of software engineering best practices, including version control, testing, and deployment.\n* Experience with model quantization, distillation or other compression techniques.\n* Excellent communication and collaboration skills.\n\n\n\nNice to Have:\n* Master's degree or PhD in Computer Science, or related field\n* Strong knowledge of C++\n* Experience with 3D graphics, computer vision, point clouds, or spatial data\n* Experience with data streaming and real-time processing frameworks such as Kafka\n* Experience with ML dataset management tooling, such as Activeloop Deeplake.\n* Experience with database technologies such as PostgreSQL, MySQL, or MongoDB.\n* Experience with big data technologies such as Snowflake, Spark, or Hive.\n* Experience with model interpretability and explainability techniques.\n* Experience with building and deploying machine learning models on edge devices or IoT devices\n\n\nWe want to hear from you! We are looking to build the best team of people who will be empowered to do their best work. If you have what it takes, but don’t necessarily meet every bullet in the job description we encourage you to apply.\n\nThe US base salary range for this full-time position is $160,000 to $294,100 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.\n\nPerks & Benefits\n* Comprehensive health plans* – 100% of premiums covered for employees & 88% of dependent premiums for US employees\n* Flexible Time Off for Exempt Employees/Generous PTO plan for Non-Exempt Employees – Take time to rest, relax and explore! Plus we offer Summer Fridays!\n* 401k,  Company ownership in the form of RSU’s & ESPP Program\n* Medical and retirement benefits vary by Country \n* For more detail visit www.matterport.com/careers \n\n\n\n\n\n\nBelief in Diversity\n\n\nAt Matterport, we don’t just accept differences, we celebrate them and recognize the value they bring to our customers and employees. Matterport is proud to be an equal opportunity workplace and works to create and support diversity at Matterport. Equal opportunity and consideration are afforded to all qualified applicants and employees. We won’t unlawfully discriminate on the basis of gender, identity or expression, race, ethnicity, religion, national origin, age, sex, marital status, physical or mental disability, veteran status, sexual orientation, and any other category protected by law. We are committed to providing employees with a work environment that provides a sense of inclusion and belonging and is free of discrimination and harassment. We also consider all qualified candidates regardless of criminal histories, consistent with legal requirements.\n\n\nMatterport is likewise committed to working with and providing reasonable accommodation to all qualified applicants and employees with disabilities in accordance with the American Disabilities Act\n\n\nFor more information regarding how Matterport collects and uses personal information, please review our Privacy Policies. https://matterport.com/privacy-policy\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Python, Testing, DevOps, Education, Cloud, Senior and Engineer jobs that are similar:\n\n $50,000 — $80,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nUnited States

About Paperspace\n\nPaperspace is a cloud computing company creating simple and scalable accelerated computing applications. Our goal is to allow individuals and professional teams to build applications with ease -  from Machine Learning to 3D graphics.\n\nPaperspace is backed by leading investors including Y Combinator, Initialized Capital, Battery Ventures, and Intel Capital.\n\nOur Team \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. 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\nThe Role\n\nIn this role, you'll be working with teams working on applied ML problems across a range of use cases such as computer vision, robotics, natural language processing, and more. Your responsibility will be to develop models for both internal and customer-facing applications with the Gradient platform. 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\nYou'll partner with Customer Support, Product, and Engineering to develop in-house ML expertise and help our customers on-board and adopt a modern MLOps methodology. You'll help drive adoption, understand innovative customer use cases, and serve as the primary problem solver in our customers' ML workflows. In addition to supporting our customers, you will have access to a cloud-scale GPU platform to research and develop state-of-the-art ML systems.\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.\n\nWhat you'll be doing\n\n• Be an expert in implementing effective, robust, and reproducible machine learning pipelines for ML teams using our platform\n• Effectively articulate best practices for instrumenting machine learning pipelines to our customers \n• Partner with our customers to uncover their desired outcomes and be the trusted advisor to help them realize the full potential of Gradient in solving their problems\n• Partner with the Sales Engineering team to ensure there's a smooth transition from POC to when a new customer is onboarded. \n• Create processes for the post-sales lifecycle (Onboarding/Training, Adoption, Workshops, Demos, etc.)\n• Develop and refine product documentation\n• Develop sample projects that can run seamlessly on the platform\n• Collaborate closely with Support, Product, and Engineering teams to influence product roadmap based on customer feedback\n• Actively use Gradient features in a variety of scenarios to provide internal product guidance\n• Contribute ideas and feedback and help prioritize feature requests and bug fixes\n• 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\n• Listen to and partner with our customers, academic users, and the broader community to understand and help prioritize their workflows in Gradient\n• Keep the organization apprised of new developments in applied & theoretical ML\n• Prototype new features for visualization and analysis in state-of-the-art deep learning research\n\nWhat we're looking for\n\n• 3+ years of experience in a professional working environment in an ML Engineer or adjacent role\n• Experience using one or more of the following packages: TensorFlow/Keras, PyTorch\n• Strong programming proficiency in Python and eagerness to help customers who are primarily users of ML/DL frameworks and tools be successful\n• Excellent communication and presentation skills, both written and verbal\n• Ability to effectively manage multiple conflicting priorities, respond promptly, and manage time effectively in a fast-paced, dynamic team environment\n• Ability to break down complex problems and resolve them through customer consultation and execution.\n• Experience with cloud platforms (AWS, GCP, Azure)\n• Experience with Linux/Unix\n• 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\n• Familiarity with a range of ML frameworks and domains (computer vision, natural language processing, reinforcement learning, statistics, etc)\n• Building internal tools and/or giving internal demos and interactive access to your ML models, e.g. sharing scripts, notebooks, or an endpoint to help your team visualize results, understand model performance, or evaluate improvement across versions\n• Caring deeply about the user experience for what you build: thinking through the details, anticipating and testing the edge cases, and considering future applications\n• Writing easy-to-follow code and effective documentation for your projects\n• Ability to clearly communicate your ideas to folks across a range of backgrounds and levels of technical knowledge\n• Strong writing and data visualization skills\n\nStrong Plus\n\n• Proficiency with one or more of the following packages: TensorFlow/Keras, PyTorch, HuggingFace, Fastai, scikit-learn, XGBoost, Jupyter, \n• Experience with hyperparameter optimization solutions\n• Experience with data engineering, MLOps, and tools such as Docker and Kubernetes\n• Experience with data pipeline tools\n• Experience as an ML educator and/or building and executing customer training sessions, product demos,\n and/or workshops at a SaaS company\n• 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• Experience contributing to architecture and systems design\n• Teaching experience\n\nWhy join us? \n\n• Top-tier machine learning teams rely on our tools for their daily work\n• This role gives you first-hand experience talking with leading researchers in the field, understanding their problems, and directly shaping the product direction.\n• Customers genuinely benefit from our tool. Over 500K users have used Paperspace, and over 22% of signups are from referrals.\n• A best-in-class product in one of the fastest-growing and largest market segments\n\nBenefits\n\n• Multiple health care insurance options with premium plans in addition to vision and dental insurance plans\n• 401(k) Plan with employer matching\n• Commuter benefits with a contribution from the company \n• Responsible Time Off Policy \n• Generous and flexible parental leave\n• Fitness & wellness benefit\n• 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 Cloud, Machine Learning, Senior, Marketing, Sales, Engineer, Front End, Teaching, Python and SaaS jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nNew York City