H2O.ai

www.h2o.ai

1 Job

319 Employees

About the Company

H2O.ai is the leading open source Generative AI and Machine Learning platform provider on a mission to democratize AI. It distills the technical prowess of 30 Kaggle Masters into straightforward AI cloud products for Generative AI and machine learning that solve powerful problems. Customers, community, and partners are strategic investors in H2O.ai building a long term vision for using AI for Good.

H2O.ai's AI Engines of distributed ML H2O-3, autoML Driverless AI, Hydrogen Torch and Document AI have transformed over 20,000 global organizations and over half of the Fortune 500 and household brands, including AT&T, Commonwealth Bank of Australia, PayPal, Chipotle, ADP, WorkDay, IFFCO-Tokio and AES. H2O.ai's AI for Good program regularly supports nonprofit groups, foundations and communities in their efforts to advance education, healthcare, and environmental conservation, including identifying areas vulnerable to natural disasters and protecting endangered species.

Join us on the movement at www.h2o.ai.

Listed Jobs

Company Name: H2O.ai
Job Title: Machine Learning Developer, Consultant
Job Description: **Job title** Machine Learning Developer, Consultant **Role Summary** Senior ML developer responsible for end‑to‑end implementation, deployment, and optimization of machine learning models in production environments. Works closely with data scientists and software engineers to transition prototypes into robust, scalable services. **Expectations** - Deliver high‑reliability, low‑latency ML services. - Apply MLOps best practices: CI/CD, automated testing, model versioning, monitoring, and performance tuning. - Collaborate with infrastructure teams for resource allocation and scalability on cloud platforms. **Key Responsibilities** - Design, build, and maintain full ML pipelines (data validation → feature engineering → model training → serving). - Deploy and integrate models using a MLOps framework; expose APIs for real‑time and batch inference. - Optimize inference performance and system throughput; profile models and adjust resource usage. - Implement monitoring for latency, accuracy drift, and system health; set automated alerts. - Maintain CI/CD pipelines, integration tests, and code reviews; enforce version control and documentation standards. - Collaborate with platform teams on containerization, orchestration, and cloud deployment strategies. **Required Skills** - Expert Python programming; strong SQL; additional experience in C/C++ or Bash preferred. - Deep knowledge of TensorFlow, PyTorch, Scikit‑learn, H2O3, and Driverless AI. - Proficient with NumPy, Pandas, Matplotlib; experience building APIs with Flask or FastAPI. - Containerization (Docker) and orchestration (Kubernetes fundamentals). - Deployment on at least one major cloud (AWS, GCP, Azure); experience with cloud ML services. - Workflow orchestration: Airflow, Kubeflow, MLflow. - ML model serving, auto‑scaling, and resource management. - Performance profiling; basic model optimization techniques. - Familiarity with large‑language models or multimodal data handling. - Strong debugging, troubleshooting, and analytical problem‑solving skills. **Required Education & Certifications** - Master’s degree in Computer Science, Engineering, or related technical field. - 4+ years professional experience building and deploying production ML systems. ---