Description

Design and build the ML platform for a global data science organization, covering data organization, model prototyping, training, and production monitoring.

This role is on-site.

Responsibilities

• Design infrastructure and implement automated workflows to streamline data-centric innovation.
• Define cohesive processes and standards to drive adoption of the ML platform across the organization.
• Collaborate with cross-functional teams to plan project execution and support model deployment and integration.
• Optimize machine learning and data transformation code for scale and robustness.
• Provide expert guidance and design support for complex data science projects.

Required Skills

• 8+ years of experience working with machine learning models and deploying them into production.
• Deep learning frameworks: TensorFlow, PyTorch, or HuggingFace.
• Big data systems: Apache Spark, Databricks, Hadoop, or similar.
• ML frameworks: Scikit-learn, SparkML, MLFlow, or Kubeflow.
• Orchestration: Batch frameworks like Airflow or streaming services.
• Cloud platforms: AWS, Google Cloud, or Azure.
• NLP, computer vision, or deep learning experience.
• Degree in Computer Science, Electrical Engineering, Data Science, or a related computational field.

Preferred Skills

• Experience with Scala, Kafka, Apache Beam, Flink, Redis, Docker, or Kubernetes.
• K knowledge of recommender systems, entity extraction, or entity resolution.

Key Skills

Education

ANY GRADUATE