Applied Machine Learning Engineer

• Build and maintain ML training pipelines and infrastructure (Vertex AI Pipelines, BigQuery, GCS) that enable data scientists to train and evaluate models

• Productionize ML models as real-time, low-latency services using Cloud Run, Vertex AI, and containerized microservices

• Set up and own monitoring, logging, and alerting for production ML services

• Develop feature engineering, embedding, and data pipelines using GCP data services

• Partner with Data Scientists and ML Researchers to take models from research to production and iterate based on real-world performance

• Build and maintain the Assistant AI product-discovery runtime: FastAPI agents, retrieval and enrichment against Search service, and turning model output into customer-facing responses

• Bachelor’s degree in Computer Science, Engineering, Math, or related field (or equivalent experience)

• 3 years of experience in ML/AI, data engineering, or software development

• 3 years of experience building, deploying, and serving real-time ML/AI models with ultra-low latency and high throughput, as resilient, scalable, cloud native services

• 2 years of experience building data engineering pipelines, ML/AI driven products or other related functions (e.g. software engineering, data science)

• 2 years of Python and SQL skills

• 2 years of experience in software design, test-driven development, and implementation using a general-purpose programming language (e.g., Python, Scala, Rust, C++, etc.)

• Solid understanding of supervised/unsupervised learning, deep learning, and Gen AI

• Master’s degree in a quantitative field plus 2 years experience in ML/AI

• 5 years of professional experience

• Experience with GCP: Vertex AI, Cloud Run, Cloud Functions, BigQuery, or GCS

• Hands-on with ML model serving (FastAPI, Vertex AI endpoints, or similar) and Docker/Kubernetes

• Familiarity with embeddings, vector search, or information retrieval systems

• Experience with monitoring and observability for production ML systems

• Exposure to PyTorch, Hugging Face Transformers, or LLMs/generative AI in production

• Competitive pay

• Great employee discount

• Financial savings and retirement resources

• Support for your physical and mental well-being