Razorfish is looking to hire a Machine Learning Engineer to design, build, and maintain production-grade ML systems across cloud platforms, translating prototypes into scalable solutions.
Requirements
- Strong proficiency in Python and SQL (2+ years)
- Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras
- Solid hands-on experience with GCP, AWS, or Azure
- Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks
- Proficient with BigQuery, Redshift, Azure Synapse
- Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka
- Experience with Airflow, Cloud Composer, Jenkins
Responsibilities
- Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)
- Develop and integrate microservices, REST APIs, and webhooks for ML model serving
- Implement CI/CD pipelines for automated model training, testing, and deployment
- Create robust data processing workflows for model training and inference
- Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)
- Implement model monitoring, versioning, and performance tracking systems
- Design automated retraining pipelines and manage model lifecycle
Other
- 3-4 years of professional experience in ML engineering, software engineering, or data science
- 2+ years of hands-on experience deploying and maintaining ML models in production
- Experience working in collaborative, cross-functional team environments
- Strong understanding of ML algorithms, model evaluation, and validation
- Excellent collaboration skills with technical and non-technical stakeholders
