Senior Machine Learning Engineer (GCP)
Core
Design, build, and deploy scalable machine learning solutions on Google Cloud Platform, operationalizing models from data ingestion to serving and monitoring.
Role type
Senior Machine Learning Engineer (GCP)
Builds
Scalable ML pipelines, production-grade models, and integrated APIs for real-time inference
Domain
Generative AI, RAG, Multimodal agents, GCP Cloud Architecture
Deliverable
production ML models
Required skills
Advanced Generative AI (RAG, Graph-based retrieval, Multimodal agents), Python (OOP, functional programming), TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark, Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow, RESTful API development (FastAPI/Flask), System Design, Distributed Systems
Preferred skills
ADK, Langchain Agentic Frameworks, Fine-tuning, Distillation, CI/CD for ML, Model governance, Explainability, GitOps
Technologies
Vertex AI, Vertex Pipelines, AutoML, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, Dataproc, Dataflow, FastAPI, Flask, TensorFlow, PyTorch, scikit-learn, pandas, NumPy, PySpark
Responsibilities
Develop, train, and optimize ML models using Vertex AI; Design and build scalable ML pipelines for feature engineering, training, evaluation, and deployment; Deploy models to production using Vertex AI endpoints; Collaborate with data scientists, data engineers, and MLOps teams; Monitor model performance and set up alerting, retraining triggers, and drift detection; Utilize GCP services in ML workflows; Apply CI/CD principles to ML models; Implement model governance, versioning, explainability, and security best practices; Document architecture decisions and workflows.
Seniority
Senior, hands-on IC
