# Software Engineer II, Machine Learning **Company:** [Poshmark](https://scaleengineer.com/companies/poshmark) Poshmark's Machine Learning Engineering team is seeking a Software Engineer II to help build and productionize machine learning infrastructure that democratizes data science across the organization. The ideal candidate will collaborate with data science and engineering teams to develop scalable ML platforms that drive value through search, personalization, fraud detection, and catalog digitization. **Role:** Machine Learning Engineer **Seniority:** Mid **Locations:** US California (Redwood City) - Office **Salary:** 120000–160000 USD [Apply](https://jobs.ashbyhq.com/poshmark/1bdf7b14-1a68-4c3b-ab64-4a3a2793b937) Canonical: https://scaleengineer.com/jobs/poshmark/software-engineer-ii-machine-learning-1bdf7b14 --- ## Responsibilities - ML Infrastructure Development: Build tools and platforms to democratize machine learning capabilities across the organization, enabling broader access and implementation of ML solutions. - Model Productionization: Collaborate with Data Science and Engineering teams to transform machine learning models into production-ready systems, ensuring scalability, performance, and reliability. - Platform Evolution: Maintain and continuously improve existing ML platforms, integrating newer technologies and architectural patterns to enhance system capabilities. ## Requirements ### education - {"name":"Computer Science or Related Field","description":"Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline"} ### technical - {"name":"Machine Learning Technologies","description":"Proficiency in machine learning libraries and frameworks such as scikit-learn, PyTorch, TensorFlow, and Spark"} - {"name":"Backend Development","description":"Experience writing backend APIs and working with distributed systems"} - {"name":"Data Processing","description":"Strong understanding of SQL and data processing techniques"} ### experience - {"name":"Software Engineering","description":"2-3 years of software engineering experience with data-intensive applications"} - {"name":"Machine Learning Lifecycle","description":"Demonstrated understanding of the machine learning development and deployment process"} ## Skills ### required - {"name":"Machine Learning Infrastructure","description":"Ability to build and maintain scalable ML platforms and tools"} - {"name":"Distributed Systems","description":"Experience with containerization and orchestration technologies"} - {"name":"Programming","description":"Strong programming skills in Python and understanding of ML engineering principles"} ### preferred - {"name":"Cloud Platforms","description":"Experience with AWS SageMaker and other cloud ML platforms"} - {"name":"Data Engineering","description":"Familiarity with data streaming and real-time processing technologies"} ## Tech stack ### tools - {"name":"Docker","description":"Containerization platform for consistent deployment"} - {"name":"Kubernetes","description":"Container orchestration system for scalable deployments"} - {"name":"MLflow","description":"Machine learning lifecycle management platform"} ### others - {"name":"Kafka","description":"Distributed event streaming platform"} - {"name":"Airflow","description":"Workflow management and scheduling platform"} ### databases - {"name":"Redis","description":"In-memory data structure store for caching and real-time operations"} - {"name":"MongoDB","description":"NoSQL database for flexible data storage"} - {"name":"Redshift","description":"Cloud data warehouse for large-scale data analytics"} ### languages - {"name":"Python","description":"Primary programming language for machine learning and backend development"} ### frameworks - {"name":"Flask","description":"Lightweight web framework for building backend services"} ## Benefits ### benefits - {"name":"Health Insurance","description":"Comprehensive medical, dental, and vision coverage"} - {"name":"Stock Options","description":"Equity compensation to align employee and company interests"} - {"name":"Professional Development","description":"Opportunities for continuous learning and skill enhancement"} ## Compensation - **max:** 160000 - **min:** 120000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Screening","description":"Phone or video call with recruitment team to discuss background and role fit"} - {"name":"Technical Assessment","description":"Online coding challenge focusing on machine learning and software engineering skills"} - {"name":"Technical Interviews","description":"Multiple rounds of interviews with ML Engineering team members, covering system design, coding, and ML concepts"} - {"name":"Final Interview","description":"Meeting with hiring manager to discuss team dynamics, role expectations, and career growth"} ## Full description ## About Poshmark **Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection.** Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury. Our AI / Machine Learning team is a central player in the Poshmark organization. Our mission is to build a world-class machine learning platform to bring value out of data for us and for our customers. Our goal is to democratize data science and machine learning, support exploding business, and use machine learning to drive value across the chain (Search, personalization, fraud detection, catalog digitization to name a few). The Machine Learning Engineering team at Poshmark is looking for an experienced machine learning engineer to take care of Poshmark’s requirement to take machine learning models with varying requirements to production .. ## **Responsibilities:** * Build tools and infrastructure to democratize ML * Productionizing ML models in collaboration with the Data Science and other Engineering teams. * Maintain and support existing platforms and evolve to newer technology stacks and architectures. ## **Desired Skills & Experience:** * 2-3 years of relevant software engineering experience with data intensive applications * Good understanding of data science concepts and machine learning lifecycle * Good understanding of spark and sql and prior experience with writing backend apis * Flexible and open to trying out newer technologies and adopting them as and when needed. ## **Technologies we use:** * Flask, Docker, Kubernetes * Redis, Redshift, MongoDB, Kafka, RabbitMQ, Kinesis * sklearn, pyTorch, Tensorflow, Spark * Mlflow, Sagemaker, Kibana, Airflow