\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

Who You Are\n\nWe are looking for a driven Software Engineer (MLOps) to be a part of our growing AI Platform team. You are bold and creative, and have deep empathy for customers who may not be tech-savvy. You will design and implement significant parts of the code base and will have the opportunity to make an immediate impact with your work and guide the product and team as we grow.\n\nYou are curious and like to understand technologies and their tradeoffs in depth - providing technical guidance to the team and peers as and when required. Leading by example, you have accumulated a wealth of insights and experiences from your hands-on involvement in the field, and you are committed to rolling up your sleeves and getting work done. You like joining and supporting other engineers in their work to learn from them as well as letting them benefit from your expertise and experience.\n\nYou have the motivation and skills to identify technical product needs, initiate projects and owning their delivery, including the involvement of engineering peers as needed. You are comfortable with challenging the status quo respectfully to drive and deliver technical excellence in the team.\n\n**We are seeking a team member located within one of the following areas: USA/Canada/UK\nResponsibilities\n\nThe AI Platform team you are joining is responsible for building the core platform that powers model training, inference and decision making in our products. Furthermore the team owns MLOps and the services hosting our AI capabilities. Productionizing results from Research, as well as extending our systems and providing support according to our customer needs fall into team responsibilities as well. You will join this team as an experienced engineer with a focus on MLOps solutions to grow our expertise in that area, but also contribute as a software engineer more widely in the team.\n\nAs an organization, we strongly believe in expertise across the stack. As such, you will experience flavors of Machine Learning, Software Engineering, Distributed Systems, MLOps and DevOps.\n\nIn particular, you will:\n\n\n* Design, build and lead the MLOps initiatives and vision for the AI Platform to strengthen automation, orchestration, versioning, observability, monitoring and collaboration for the platform.\n\n* Build and design scalable components for the AI Platform to allow high throughput training and inference for RL agents doing realtime inference for autonomous control of industrial systems.\n\n* Contribute to the design and implementation of the product backend by writing REST & gRPC API services and scalable event-driven backend applications.\n\n* Design clear, extensible software interfaces for the team's customers and maintain a high release quality bar.\n\n* Design and optimize data storage & retrieval mechanisms for high throughput, security & ease of access.\n\n* Perform DevOps duties of CI/CD, Release & Deployment management.\n\n* Be a part of our global production oncall team and, own & operate your services in production, meeting Phaidra’s high bar for operational excellence.\n\n* Lead cross-functional initiatives collaborating with engineers, product managers and TPM across teams.\n\n* Mentor your peers and be a technical role-model in the team.\n\n\n\nOnboarding\n\nIn your first 30 days…\n\n\n* You will be immersed in an onboarding program that introduces you to Phaidra and our product.\n\n* You will spend time in the Engineering org, learning how the teams operate, interact, and approach problems.\n\n* You will read various parts of our handbook and familiarize yourself with the documentation culture at Phaidra.\n\n* You will set up your development environment and start working on an onboarding exercise that will introduce you to various parts of our code base.\n\n* You will learn about how we use agile and be able to navigate our sprint boards and backlogs.\n\n* You will learn about various team standards and development & release processes.\n\n* You will start to learn about our system architecture and infrastructure.\n\n* You will start picking up few good “first-tasks” to get yourself accustomed to the end to end release flow.\n\n\n\n\nIn your first 60 days…\n\n\n* You will get a solid understanding of what Phaidra does and how we do it.\n\n* You will meet with team members across Phaidra and started building relationships that will help you be successful at your job.\n\n* You will complete the onboarding exercise and will be on your way to completing your first production task.\n\n* You will take ownership for the MLOps work on the team, identify gaps and propose roadmap items on the topic.\n\n\n\n\nIn your first 90 days…\n\n\n* You will be fully integrated in the team and with team members across the company.\n\n* You will have a more in-depth understanding of our system architecture and infrastructure.\n\n* You will complete your first on-call experience helping monitor and improve our production environments.\n\n* You will become an expert with our tooling.\n\n* You will start to contribute to knowledge sharing throughout Phaidra and the team.\n\n* You will take proactively drive MLOps topics in the team and represent it technically throughout the company.\n\n\n\nKey Qualifications\n\n\n* 7+ years of work experience.\n\n* Bachelors or Masters in Computer Science, or equivalent experience.\n\n* Strong experience on designing and implementing MLOps solutions for AI production systems\n\n* Expertise with production Software Engineering - relational and non-relational data modelling, micro-services, understanding of event driven systems, etc.\n\n* Strong experience building large scale multi-tenant systems with high availability, fault tolerance, performance tuning, monitoring, and statistics/metrics collection.\n\n* Strong expertise in Python and Cloud environments\n\n* Good grasp of Machine Learning (especially Deep Learning) fundamentals.\n\n* Ability to collaborate and communicate effectively in an all-remote setting\n\n* Doing your work with curiosity, ownership, transparency & directness, outcome orientation, and customer empathy.\n\n\n\nBonus\n\n\n* Experience as a service owner of a realtime production system - operating & monitoring services in production, including using observability tooling such as Prometheus, Grafana, Tempo or equivalent offerings and incident management.\n\n* Experience with building applications that can be deployed in cloud, hybrid or on prem environments\n\n* Exposure to Reinforcement Learning\n\n\n\nOur Stack\n\n\n* Languages - (Backend) Python, Go; (Frontend) JavaScript/TypeScript, React; Customer SDK & Clients - C# .NET\n\n* PyTorch\n\n* Cypress\n\n* Docker, Kubernetes, Terraform & Kapitan\n\n* Gitlab CI, ArgoCD, Atlantis, Vercel\n\n* GCP - GKE, PubSub, CloudSQL, BigTable, Postgres, etc.\n\n* Ray.io\n\n* REST & gRPC micro-services\n\n* Poetry, Pantsbuild\n\n\n\nGeneral Interview Process\n\nAll of our interviews are held via Google Meet, and an active camera connection is required.\n\n* Initial screening interview with a People Operations team member (30 minutes): The purpose of this interview is to meet you, learn more about your background, and discuss what you are looking for in a new position.\n\n* Hiring manager interview (30 minutes): The purpose of this meeting is for you to get to know the manager for the role. This chat will mainly focus on your previous experience and technical background. You can expect to talk about projects that you have worked on in the past and ask any questions about the team & role.\n\n* Technical Interview 1 (60 minutes): The purpose of this interview is to assess your skills in Machine Learning and related mathematics.\n\n* Technical Interview 2 (90 minutes): In this interview, we will go over a real world MLOps problem. You can expect to draw architecture diagrams using boxes & arrows in your browser. We will talk about system design, scalability and monitoring.\n\n* Meeting with VP of Engineering (30 minutes): This interview is a combination of technical and cultural fit assessment. You will cover the technical experience and the skills that you brinand have an opportunity to ask any questions about the team’s culture or vision.\n\n* Culture fit interview with Phaidra’s co-founders (30 minutes): This interview focuses on alignment with Phaidra’s values\n\n\nBase Salary\n\nUS Residents: $115,200-$208,800/year\n\nUK Residents: £96,400-£144,000/year\n\nThis position will also include equity.\n\nThese are best faith estimates of the base salary range for this position. Multiple factors such as experience, education, level, and location are taken into account when determining compensation. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Python, DevOps, Cloud, API, Senior, Engineer and Backend jobs that are similar:\n\n $65,000 — $110,000/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\nSeattle, Washington, United States

\nMemora Health works with leading healthcare organizations to make complex care journeys simple for patients and clinicians so that care is more accessible, actionable, and always-on. Our team is rapidly growing as we expand our programs to reach more health systems and patients, and we are excited to bring on a Senior Data Engineer. \n\nIn this role, you will have the responsibility of driving the architecture, design and development of our data warehouse and analytics solutions, alongside APIs that allow other internal teams to interact with our data. The ideal candidate will be able to collaborate effectively with Memora’s Product Management, Engineering, QA, TechOps and business stakeholders.\n\nThis role will work closely with the cross-functional teams to understand customer pain points and identify, prioritize, and implement maintainable solutions. Ideal candidates will be driven not only by the problem we are solving but also by the innovative approach and technology that we are applying to healthcare - looking to make a significant impact on healthcare delivery. We’re looking for someone with exceptional curiosity and enthusiasm for solving hard problems.\n\n Primary Responsibilities:\n\n\n* Collaborate with Technical Lead, fellow engineers, Product Managers, QA, and TechOps to develop, test, secure, iterate, and scale complex data infrastructure, data models, data pipelines, APIs and application backend functionality.\n\n* Work closely with cross-functional teams to understand customer pain points and identify, prioritize, and implement maintainable solutions\n\n* Promote product development best practices, supportability, and code quality, both through leading by example and through mentoring other software engineers\n\n* Manage and pare back technical debts and escalate to Technical Lead and Engineering Manager as needed\n\n* Establish best practices designing, building and maintaining data models.\n\n* Design and develop data models and transformation layers to support reporting, analytics and AI/ML capabilities.\n\n* Develop and maintain solutions to enable self-serve reporting and analytics.\n\n* Build robust, performant ETL/ELT data pipelines.\n\n* Develop data quality monitoring solutions to increase data quality standards and metrics accuracy.\n\n\n\n\nQualifications (Required):\n\n\n* 3+ years experience in shipping, maintaining, and supporting enterprise-grade software products\n\n* 3+ years of data warehousing / analytics engineering\n\n* 3+ years of data modeling experience\n\n* Disciplined in writing readable, testable, and supportable code in JavaScript, TypeScript, Node.js (Express), Python (Flask, Django, or FastAPI), or Java.\n\n* Expertise writing, and consuming RESTful APIs\n\n* Experience with relational or NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis, etc.)\n\n* Experience with Data Warehouses (BigQuery, Snowflake, etc.)\n\n* Experience with analytical and reporting tools, such as Looker or Tableau\n\n* Inclination toward test-driven development and test automation\n\n* Experience with scrum methodology\n\n* Excels in mentoring junior engineers\n\n* B.S. in Computer Science or other quantitative fields or related work experience\n\n\n\n\nQualifications (Bonus):\n\n\n* Understanding of DevOps practices and technologies (Docker, Kubernetes, CI / CD, test coverage and automation, branch and release management)\n\n* Experience with security tooling in SDLC and Security by Design principles\n\n* Experience with observability and APM tooling (Sumo Logic, Splunk, Sentry, New Relic, Datadog, etc.)\n\n* Experience with an integration framework (Mirth Connect, Mule ESB, Apache Nifi, Boomi, etc..)\n\n* Experience with healthcare data interoperability frameworks (FHIR, HL7, CCDA, etc.)\n\n* Experience with healthcare data sources (EHRs, Claims, etc.)\n\n* Experience working at a startup\n\n\n\n\n\n\nWhat You Get:\n\n\n* An opportunity to work on a rapidly scaling care delivery platform, engaging thousands of patients and care team members and growing 2-3x annually\n\n* Enter a highly collaborative environment and work on the fun challenges of scaling a high-growth startup\n\n* Work alongside world-class clinical, operational, and technical teams to build and scale Memora\n\n* Shape how leading health systems and plans think about modernizing the care delivery experience for their patients and care teams\n\n* Improve the way care is delivered for hundreds of thousands of patients\n\n* Gain deep expertise about healthcare transformation and direct customer exposure with the country’s most innovative health systems and plans\n\n* Ownership over your success and the ability to significantly impact the growth of our company\n\n* Competitive salary and equity compensation with benefits including health, dental, and vision coverage, flexible work hours, paid maternity/paternity leave, bi-annual retreats, Macbook, and a 401(k) plan\n\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, DevOps, NoSQL, Senior, Engineer and Backend jobs that are similar:\n\n $60,000 — $110,000/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