Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s
leading agentic AI company, H2O.ai converges Generative and Predictive AI to
help enterprises and public sector agencies develop purpose-built GenAI
applications on their private data. Its open-source technology is trusted by
over 20,000 organizations worldwide - including more than half of the Fortune
500 - H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank
of Australia, Singtel, Chipotle, Workday, Progressive Insurance, and NIH.
H2O.ai partners include Dell Technologies, Deloitte, Ernst & Young (EY), NVIDIA,
Snowflake, AWS, Google Cloud Platform (GCP) and VAST. H2O.ai’s AI for Good
program supports nonprofit groups, foundations, and communities in advancing
education, healthcare, and environmental conservation. With a vibrant community
of 2 million data scientists worldwide, H2O.ai [http://h2o.ai/] aims to
co-create valuable AI applications for all users.
H2O.ai has raised $256 million from investors, including Commonwealth Bank,
NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York
Life.
About This Opportunity
We are seeking a Senior ML Developer Consultant with strong software engineering
skills and practical experience taking Machine Learning models to production.
This role focuses on building, deploying, and optimizing robust ML-powered
features and applications, requiring a hands-on approach to MLOps, system
integration, and performance tuning. The ideal candidate will be a
high-contributing individual who can bridge the gap between Data Science
prototypes and reliable, scalable production systems.
What You Will Do
ML System Implementation & Development
- 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.
Software Engineering & MLOps
- 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.
What We Are Looking For
Core Programming & ML Fundamentals
- Proficiency in Python: Expert-level proficiency in Python and strong command
of SQL. Working knowledge of C/C++ or Bash is a plus.
- ML Frameworks: Deep experience with key ML frameworks: TensorFlow, PyTorch,
Scikit-learn, H2O3, and Driverless AI.
- Data Libraries: Extensive, hands-on experience with core data processing
libraries: NumPy, Pandas, and Matplotlib.
- Application Development: Proven experience building applications and APIs
using modern frameworks (e.g., Flask or FastAPI).
MLOps and Infrastructure
- Containerization & Orchestration: Strong practical experience with Docker and
foundational knowledge of Kubernetes for deployment.
- Cloud Platforms: Experience deploying and operating ML workloads on at least
one major cloud provider (e.g., AWS, GCP, or Azure).
- Workflow Tools: Experience with ML workflow orchestration tools such as
Airflow, Kubeflow, or MLflow.
- Software Practices: Strong software development practices, including Git,
unit testing, code review, and experience with microservices architecture.
Advanced Capabilities (Hands-On)
- 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.
Experience & Professional Skills
- Education & Experience: 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.
- Problem-Solving: Strong debugging, troubleshooting, and analytical skills for
diagnosing and resolving production system issues.
- Collaboration: Proven ability to collaborate effectively with data scientists
and software engineers to transition experimental models into reliable
production code.
- Delivery Focus: Track record of driving projects to completion and meeting
strict performance requirements.
Why H2O.ai?
- Market leader in total rewards
- Remote-friendly culture
- Flexible working environment
- Be part of a world-class team
- Career growth
- This is a one year contract opportunity
H2O.ai is committed to creating a diverse and inclusive culture. All qualified
applicants will receive consideration for employment without regard to their
race, ethnicity, religion, gender, sexual orientation, age, disability status or
any other legally protected basis.
H2O.ai is an innovative AI cloud platform company, leading the mission to
democratize AI for everyone. Thousands of organizations from all over the world
have used our cutting-edge technology across a variety of industries. We’ve made
it easy for people at all levels to generate breakthrough solutions to complex
business problems and advance the discovery of new ideas and revenue streams. We
push the boundaries of what is possible with artificial intelligence.
H2O.ai employs the world’s top Kaggle Grandmasters, the community of
best-in-the-world machine learning practitioners and data scientists. A strong
AI for Good ethos and responsible AI drive the company’s purpose.
Please visit [http://www.h2o.ai/]www.H2O.ai [http://www.h2o.ai/] to learn more.
