Python AI/ML Engineer

About the job

Job Summary (List Format) • Implement distributed machine learning (ML) experimentation and training platforms for firm-wide use, adhering to architectural requirements. • Develop and support tools/workflows for ML experiments, automated training, and production deployments. • Extend ML libraries/frameworks to enable advanced experimentation, training, and serving. • Design and deliver APIs and SDKs for improved data scientist experience on the ML platform. • Collaborate with infrastructure, product management, and security/compliance teams to deliver robust, tailored solutions. • Apply knowledge of Python and ML frameworks (e.g., Ray, TensorFlow, PyTorch, Scikit-Learn) in development and operations. • Utilize public cloud (especially AWS) for ML workflows including featurization, training, deployment, and monitoring. • Ensure operational stability through hands-on system design, application development, and testing. • Leverage experience in DevOps and containerization tools (Docker, Jenkins, Spinnaker, Terraform, Kubernetes). • (Preferred) Apply knowledge of Big Data technologies (Hadoop, Spark, Airflow) and AWS ML stack (SageMaker, EMR). • Require 4+ years experience with Generative AI, and formal training/certification in ML concepts. Let me know if you need a more concise or tailored summary!

Requirements

• Machine Learning
• Python
• DevOps
• TensorFlow
• PyTorch

Qualifications

• 4+ years experience with Generative AI

Preferred Technologies

• Machine Learning
• Python
• DevOps
• TensorFlow
• PyTorch