Applied Scientist​/Machine Learning Engineer, Gaia

How we work - Locations & Flexible Working:
Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives. The Interview Process:
Our process is clear and respectful of your time:
Initial

Relevance is based on skills and concepts — not a guarantee that you qualify.

Covered skills: AI fundamentals Machine learning Deep learning LLM evaluation

Skills to close:
None listed

Coming-soon courses matched to this posting — outline, waitlist, and skill path.

Transform messy operational data into reliable inputs for AI systems through robust pipeline architecture.

Choose appropriate AI approaches and design deployment architectures that meet latency, cost, and reliability requirements.

Embed AI outputs into existing workflows where users can act on them effectively and provide feedback.

Add constraints and verification layers that prevent hallucinations, errors, and out-of-bounds outputs.

Measure what matters by designing evaluation systems that track accuracy, business impact, and failure modes.

Design systems that capture user feedback and operational signals to improve model performance over time.

Establish processes that make AI systems auditable, maintainable, and understandable to non-technical stakeholders.

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