Senior ML Developer, Consultant

Posted 20 Days Ago
Be an Early Applicant
Toronto, ON
In-Office
Senior level
Artificial Intelligence • Big Data • Machine Learning • Software • Analytics
The Role
The Senior ML Developer Consultant will implement and maintain ML pipelines, deploy and optimize models, build APIs, and enforce MLOps best practices.
Summary Generated by Built In
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 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 www.H2O.ai to learn more.

Top Skills

Airflow
AWS
Azure
Bash
C/C++
Docker
Driverless Ai
Fastapi
Flask
GCP
Git
H2O3
Kubeflow
Kubernetes
Matplotlib
Mlflow
Numpy
Pandas
Python
PyTorch
Scikit-Learn
SQL
TensorFlow
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The Company
Mountain View, CA
321 Employees
Year Founded: 2012

What We Do

H2O.ai is the leading AI cloud company, on a mission to democratize AI for everyone. Customers use the H2O AI Hybrid Cloud platform to rapidly make, operate and innovate to solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI partner to more than 20,000 global organizations, including AT&T, Aegon/ Transamerica, Allergan, Bon Secours Mercy Health, Capital One, Commonwealth Bank of Australia, GlaxoSmithKline, Hitachi, Kaiser Permanente, PayPal, PWC and Walgreens, over half of the Fortune 500 and one million data scientists. Goldman Sachs, NVIDIA and Wells Fargo are not only customers and partners, but strategic investors in the company. H2O.ai’s customers have honored the company with a Net Promoter Score (NPS) of 78— the highest in the industry based on breadth of technology and deep employee expertise. The world’s top 20 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are employees of H2O.ai. A strong AI for Good ethos to make the world a better place and Responsible AI drive the company’s purpose. Please join our movement at www.H2O.ai.

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