
Machine Learning Engineer
20 hours ago
Pursue a career as a Machine Learning Operations Engineer with our organization.
Key Responsibilities:- Develop, deploy, and maintain scalable machine learning models on cloud platforms such as AWS or GCP.
- Build efficient continuous integration and delivery pipelines for machine learning workflows using GitHub Actions or cloud-native tools.
- Containerize and orchestrate workloads with Docker and Kubernetes; manage infrastructure via Terraform or CloudFormation.
- Implement model registries, feature stores, and observability using MLflow, Feast, and Prometheus/Grafana.
You will collaborate with data scientists to operationalize machine learning models for personalization, recommendations, and natural language processing.
Proficiency in Python, machine learning frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL) is required.
Bonus: experience with real-time machine learning serving, A/B testing, or media/recommender systems.
Responsibilities Include:
- Spearheading the deployment, monitoring, and scaling of machine learning models across various cloud platforms.
- Crafting and maintaining seamless continuous integration and delivery pipelines for machine learning workflows.
- Designing and implementing robust containerization and orchestration strategies with Docker and Kubernetes.
- Fostering collaboration between data scientists to drive model operationalization for enhanced business outcomes.
Necessary Skills:
- Strong background in machine learning operations and data science.
- Expertise in Python programming and machine learning frameworks.
- Proficiency in data pipelines and storage solutions.
- Experience with cloud platforms (AWS, GCP) and containerization/orchestration tools (Docker, Kubernetes).
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