2 months ago
Germany (city not specified)Mid Level
Responsibilities
- Build and integrate AI applications across frontend, backend, data, and AI components.
- Develop backend services and APIs supporting AI functionality and data integration.
- Create user interfaces for complex AI-powered applications using frontend frameworks.
- Develop and fine-tune machine learning and LLM solutions.
- Deploy and scale AI models and applications in cloud-based production environments.
- Use modern development tools and AI-assisted coding platforms to improve productivity and code quality.
- Collaborate with the Kaggle GM team to take AI solutions from concept to market.
Requirements
- Proven experience as a Full Stack Engineer or in a similar software development role.
- Hands-on experience with data engineering, machine learning model development, and full-stack application development.
- Core proficiency in Python and some experience with JavaScript.
- Proficiency in PyTorch and basic understanding of fine-tuning deep learning models, particularly LLMs.
- Experience with FastAPI, SQL, NoSQL, S3, React, Next.js, Docker, Kubernetes, cloud services, and OpenAI API endpoints.
- Bachelor's, master's, or PhD degree in Computer Science, Engineering, or a related field is preferred but not mandatory.
- Experience contributing to open-source projects and a public track record of AI experience.
- Advanced deep learning knowledge, preferably with a focus on Natural Language Processing.
- Demonstrated success bringing AI solutions from concept to market and adapting to new technologies.
Benefits
- Remote-friendly culture and a flexible working environment.
- Career growth opportunities and participation on a world-class team.
- Inclusive workplace committed to equal consideration for qualified applicants.
- Preferred location is Europe, with DACH highly preferred.
Tech Stack
Categories
About H2O.ai
H2O.ai builds open-source and commercial platforms for machine learning and generative AI, used by enterprises and public-sector teams to develop models and applications on private data. Its portfolio includes H2O-3, Driverless AI, and tools for LLM fine-tuning and deployment, offered via subscriptions and cloud services. Founded in 2012 and headquartered in Mountain View, it is privately held; customers include AT&T, Commonwealth Bank of Australia, Workday, and the NIH.