Lead Machine Learning Engineer

What you'll do

• Build and maintain pipelines for distributed model training on GPU-enabled clusters.
• Develop and manage pipelines for model promotion and Machine Learning Development Life Cycle (MDLC) capabilities.
• Optimize training throughput for large-scale data sources.
• Establish and maintain integrations for model monitoring and observability platforms.
• Design and develop ML frameworks and components for various model implementations.
• Monitor models in production to ensure reliability, security, and scalability.
• Improve data quality and feedback loops to reduce agent effort and shorten resolution times.

What we're looking for

• BS in Computer Science or related Engineering field with 6+ years of experience.
• MS degree in Computer Science or related Engineering field with 4+ years experience.
• Solid knowledge and extensive experience in Python, cloud computing, and ML frameworks like PyTorch or TensorFlow.
• Deep knowledge and passion for data science fundamentals, including training and deploying models.
• Experience in monitoring and observability tools to monitor model input/output and feature statistics.
• Operational experience in big data/ML tools such as Ray, Spark, and training/inference systems like Ray, vllm/SGLang.
• Solid grounding in engineering fundamentals and enterprise system design.
• Experience with recommendation and personalization systems (preferred).
• CUDA experience (preferred).
• Experience in containers (Docker), container orchestration (Kubernetes, ECS), and DAG orchestration (Airflow, Kubeflow) (preferred).
• Good knowledge of data storage solutions and strategies (preferred).