[Remote] Machine Learning Developer, Consultant

Note: The job is a remote job and is open to candidates in USA. H2O.ai is a leading AI company dedicated to democratizing AI through innovative solutions. They are seeking a Senior ML Developer Consultant to implement and optimize machine learning systems, focusing on deploying ML models and integrating them into existing architectures. Responsibilities • End-to-End Pipeline Implementation: Implement and maintain end-to-end Machine Learning pipelines, focusing on robustness from data validation through to serving • Model Deployment: Deploy, integrate, and maintain production ML models using H2O MLOps framework, ensuring high reliability, low latency, and efficient performance • Feature Integration: Develop efficient data processing pipelines and integrate models with existing data architectures (data warehouses, feature stores) • Performance Optimization: Optimize model inference and system throughput for specific application requirements • Application Development: Build Python-based APIs and microservices for real-time and batch model prediction • MLOps Practices: Implement and enforce MLOps best practices, including continuous integration/continuous deployment (CI/CD), automated testing, and proper model versioning • Monitoring: Set up and maintain monitoring for deployed models, tracking performance, data drift, and system health • Infrastructure Collaboration: Work closely with infrastructure and platform teams to ensure optimal resource allocation and scalability on cloud platforms Skills • Expert-level proficiency in Python and strong command of SQL • Working knowledge of C/C++ or Bash is a plus • Deep experience with key ML frameworks: TensorFlow, PyTorch, Scikit-learn, H2O3, and Driverless AI • Extensive, hands-on experience with core data processing libraries: NumPy, Pandas, and Matplotlib • Proven experience building applications and APIs using modern frameworks (e.g., Flask or FastAPI) • Strong practical experience with Docker and foundational knowledge of Kubernetes for deployment • Experience deploying and operating ML workloads on at least one major cloud provider (e.g., AWS, GCP, or Azure) • Experience with ML workflow orchestration tools such as Airflow, Kubeflow, or MLflow • Strong software development practices, including Git, unit testing, code review, and experience with microservices architecture • Experience working with large language models (LLMs) or multimodal data (text, images, time-series) in an applied setting, including experience with H2OGPTe • Familiarity with model serving patterns, auto-scaling, and resource management in a production context • Experience with performance profiling and basic model optimization techniques • Master's degree in Computer Science, Engineering, or a related technical field, plus 4+ years of professional experience building and deploying production software/ML systems • Strong debugging, troubleshooting, and analytical skills for diagnosing and resolving production system issues • Proven ability to collaborate effectively with data scientists and software engineers to transition experimental models into reliable production code • Track record of driving projects to completion and meeting strict performance requirements Benefits • Market leader in total rewards • Remote-friendly culture • Flexible working environment • Be part of a world-class team • Career growth Company Overview • H2O.ai is a machine learning platform that builds smart applications. It was founded in 2012, and is headquartered in Mountain View, California, USA, with a workforce of 201-500 employees. Its website is Apply tot his job