AI/ML Engineer

Open position

Stockholm, Sweden·Full-time

[THE ROLE]

What this work looks like

Applied AI is core to how Vantir consults and how we build with founders. This role is for engineers who put LLM and ML systems into production: retrieval, agents, evaluation, inference, and the unglamorous work that makes them reliable.

We cut through hype. You will be asked to ship systems that hold up under real users, real data, and real cost constraints.

What you'll do

Design and ship LLM and agentic systems, tool use, retrieval, orchestration, with evaluation, not vibes, as the release bar.
Own production inference: serving, latency, cost, observability, and failure modes.
Build evaluation harnesses and feedback loops so quality is measured, not assumed.
Work across the stack with data and software engineers so models have clean inputs and a real home in the product.
Help clients and ventures separate useful AI from theater, including in technical due diligence.

What we're looking for

Hands-on experience shipping ML or LLM systems past the demo: APIs, pipelines, or product features in production.
Comfort with modern LLM application patterns (retrieval, tool-calling / agents, structured output) and their failure modes.
MLOps instincts: versioning, CI for models and prompts, monitoring, and rollback.
Strong software engineering in Python, and ideally TypeScript, plus cloud deployment.
You care about evaluation as much as architecture.
Fluent with modern AI development tooling as part of your daily engineering workflow.

Nice to have

Fine-tuning, distillation, or custom model work when the use case actually needs it.
Vector search, RAG at scale, or agent systems in production.
GPU / inference optimization, batching, or cost control at meaningful volume.
Client-facing consulting or startup product work.

[HOW WE WORK]

How this role fits Vantir

Invent and simplify. We don't add an agent because the slide looks better; we add one when it beats the simpler system. You'll have ownership of production behavior, a bias for action, and the chance to build with founders who need AI that actually works, not a prototype that impresses a room once.

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AI/ML Engineer

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