Advance AI Capabilities: Enhance Ask Gordon's ability to understand complex technical questions and provide accurate, actionable responses about Docker, containerization, and development workflows

RAG System Enhancement: Improve our Retrieval-Augmented Generation pipeline to better understand Docker documentation, code repositories, and technical knowledge sources

Evaluation & Testing: Design and implement robust evaluation frameworks to measure AI performance, accuracy, and user satisfaction

Model Development & Fine-tuning: Train, fine-tune, and optimize language models specifically for Docker's technical domain and use cases

Rapid Prototyping: Iterate quickly on new AI features and capabilities, moving from concept to production efficiently

Cross-functional Collaboration: Work closely with product managers, designers, and other engineers to integrate AI capabilities seamlessly into Docker's developer experience

AI/ML Expertise: 3+ years of hands-on experience with machine learning models, particularly large language models (LLMs)

RAG Systems: Practical experience building and optimizing Retrieval-Augmented Generation systems

Model Training & Fine-tuning: Proven experience training, fine-tuning, or adapting models for specific domains or use cases

Evaluation Frameworks: Experience designing and implementing AI evaluation methodologies and metrics

Programming Skills: Proficiency in Go (primary at Docker) and Python

AI Frameworks: Experience with LangChain/LangGraph or similar AI orchestration frameworks

Rapid Iteration: Demonstrated ability to prototype quickly and iterate based on user feedback

Experience with containerization technologies (Docker, Kubernetes) or developer tooling (preferred)

Knowledge of vector databases and semantic search technologies (preferred)

Experience with AI safety, hallucination detection, and reliability techniques (preferred)

Integrate into our dynamic AI engineering team building intelligent developer assistance

Deepen knowledge of Ask Gordon's architecture, Docker's AI platform, and our technical stack

Contribute to your first AI model improvements or RAG system enhancements with the help of your team

Understand our evaluation frameworks and begin analyzing AI performance metrics

Continue to enhance and optimize our AI models and systems

Improve our RAG pipeline and evaluation frameworks

Deepen your knowledge of Docker's ecosystem and developer workflows

Help other new team members onboard

Regularly interact with internal stakeholders and analyze user feedback

Lead significant AI capability improvements that directly impact millions of Docker users

Continue to help grow the team and develop more efficient AI development processes

Embrace data-driven tracking and reporting of how AI features increase developer productivity

Contribute to model fine-tuning and performance optimization across our AI platform

Grow your skills beyond AI modeling into enterprise-grade AI system architecture and deployment

Drive initiatives to expand Ask Gordon's capabilities for enterprise use cases

In collaboration with your manager, you will have a Career Development Plan that will outline your trajectory beyond your first year

Freedom & flexibility; fit your work around your life

Designated quarterly Whaleness Days

Home office setup; we want you comfortable while you work

16 weeks of paid Parental leave

Technology stipend equivalent to $100 net/month

PTO plan that encourages you to take time to do the things you enjoy

Quarterly, company-wide hackathons

Training stipend for conferences, courses and classes

Equity; we are a growing start-up and want all employees to have a share in the success of the company

Docker Swag

Medical benefits, retirement and holidays vary by country