Description

Design and build the ML platform for a global 40+ person data science organization, covering data organization, model prototyping, training, and production monitoring.

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 such as TensorFlow, PyTorch, or HuggingFace.
• Expertise in Apache Spark, Databricks, Hadoop, or similar big data systems.
• Machine learning frameworks including Scikit-learn, SparkML, MLFlow, or Kubeflow.
• Batch orchestration frameworks like Airflow or streaming services.
• Cloud platform technologies including 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.
• Knowledge of recommender systems, entity extraction, or entity resolution.

Key Skills

Education

ANY GRADUATE