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. With a focus on Sovereign AI—secure, compliant, and infrastructure-flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control.
Our 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, Chipotle, Workday, Progressive Insurance, and NIH.
H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. 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.
For more information, visit www.h2o.ai.
About This Opportunity
H2O.ai is at the forefront of the rapidly evolving Generative & Predictive landscape. We're leveraging MLOps to transform machine learning models from isolated, engineer-specific tools into robust, cloud-native services that are scalable and consistently available. Our approach is firmly rooted in Kubernetes, positioning our team at the cutting edge of cloud solutions.
As a Machine Learning Engineer within the H2O.ai Professional Services team, the role necessitates close collaboration with the client's technical teams and internal stakeholders, encompassing Customer Success, Enterprise Support, and Product Engineering departments.
This position is based in Sri Lanka.
What You Will Do
- Deliver data science and/or machine learning professional services to the customer.
- Develop and implement end-to-end machine learning workflows, from data ingestion to model deployment and monitoring
- Build and optimize Generative AI applications leveraging Large Language Models (LLMs) and other foundation models
- Create agentic AI systems for workflow automation and complex task execution
- Collaborate with cross-functional teams to integrate ML solutions into customer environments
- You will also be responsible for working closely with customer/H2O solution engineers/architects to implement end to end AI solutions with the ultimate goal of deploying the model to production. Your focus would be on the data science/modelling part of the solution.
- Demonstrate machine learning solutions with engaging storytelling and technical accuracy.
- Architect, design, and deliver Machine Learning and Data Science solutions.
- Present at meetups and webinars in the Data Science community, and be an integral part of the Maker culture of creating the best products and solutions.
- Proven experience in data science, machine learning, and AI with a minimum of 4+ years of hands-on experience.
- Experience with Generative AI applications, including working with LLMs, prompt engineering, and fine-tuning including deployment of end to end ML pipelines
- Practical knowledge of Retrieval Augmented Generation (RAG) and vector databases
- Experience developing agentic AI systems for workflow automation
- Familiarity with model monitoring, observability, and performance optimization
- Strong understanding of software engineering best practices and system design
- Strong problem-solving skills and the ability to work independently and as part of a team.
- Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Experience with H2O.ai products (H2O MLOps, Driverless AI, h2oGPT)
- Experience with cloud platforms (AWS, GCP, Azure) and their ML services
- Contributions to open-source ML/AI projects
- Experience with model governance, responsible AI, and implementing guardrails for LLMs.
- Market leader in total rewards
- Remote-friendly culture
- Flexible working environment
- Be part of a world-class team
- Career growth
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