Senior Software Engineer II, Machine Learning

About the Role

The 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 digitisation to name a few).

Responsibilities

• Manage the entire ML lifecycle from data collection to deployment and monitoring
• Collaborate across teams such as DS, QA, Infra and other engineering teams to productionize ML models
• Write and optimize code for production environments, ensuring the robustness and reliability of ML services at scale
• Manage and support current solutions while evolving them to incorporate newer technologies
• Convey complex concepts in a clear and simple manner through strong written, verbal, and presentation skills
• Stay updated with the latest developments in data science and machine learning

Desired Skills & Experience

• 4+ years of experience applying Machine Learning to concrete problems at large scale
• Bachelors or Masters in Computer Science, Statistics, or related field
• Strong CS fundamentals with the ability to write algorithms with ease
• Solid understanding of Data Science and ML fundamentals – Regression, Classification, Tree-based approach, Neural network, and sequence-based models
• Working experience with at least one ML model: LLMs, GNN, Deep Learning, Logistic Regression, Gradient Boosting trees, etc.
• Excellent understanding of the ML lifecycle
• Good understanding of system architecture and knowledge of big data technologies (streaming architecture, data pipelines, etc.)
• Experience with Python, SQL, Java or Scala

Good to Have

• Big data systems: Spark, EMR, S3, AirFlow
• Production experience with LLMs and prompt engineering
• Experience with Flask, FastAPI, RabbitMQ, Embeddings and Vector DBs

Tech Stack

• PyTorch, TensorFlow, Scikit-learn
• Flask, FastAPI, Gunicorn, Quarkus
• MLFlow, SageMaker, Kibana, Airflow, Databricks, Grafana, Datadog
• Docker, Kubernetes, Jenkins
• Redis, Redshift, MongoDB, Spark, Kafka, RabbitMQ, Milvus