Senior Machine Learning Engineer
Full-time | Munich | Seed Stage | Equity + Salary
Help Build a Generational Company
At Knowlix, we’re on a mission to 10x small businesses' productivity. We strive to become the dominant small business platform for human-AI and AI-to-AI collaboration.
We’re still early, but we’re thinking big. This is your opportunity to help shape a product that serves millions and defines a category.
We move fast, ship often, and obsess over quality. If you burn to build, ship, and scale - and you love using AI to make things radically better - this is your seat at the table.
Why Knowlix, Why Now
We're a well-funded seed-stage startup, backed by top-tier investors and experienced founders
Our tech works - and first users are already feeling the first magic
We're going after a massive market, with a product that changes how people work
You’ll be joining as one of the earliest team members - with real influence and ownership over the trajectory of the company
We believe speed is a function of focus + iteration
This isn’t a job. It’s a chance to help build a once-in-a-generation company if we do things right.
The Role
You will design and ship advanced ML systems - especially LLM-driven agents and self-improving workflows. You’ll build robust data and training pipelines, enable fast experimentation, and ensure models and agents continuously improve in production. This is a hands-on role in a fast-moving startup where you ship, measure, and iterate quickly.
What You'll Do
Build LLM-based agents, tool-using workflows, and autonomous self-improvement loops.
Design, train, and evaluate ML models across NLP/LLM, vision, and retrieval domains.
Develop data pipelines, training code, experiment tooling, and automated deployment systems.
Use PyTorch for model development and W&B (or similar) for tracking experiments and lineage.
Implement monitoring for performance, drift, safety, and agent behavior.
Optimize inference for latency, throughput, and cost.
Work closely with engineering and product to turn prototypes into reliable production features.
Establish ML engineering best practices and mentor teammates.
What You Bring (Requirements)
5+ years experience deploying ML systems to production.
Strong Python and deep experience with PyTorch.
Hands-on experience with LLMs, retrieval (RAG), tool-use, or agent frameworks (e.g., LangGraph, AutoGen).
Strong command of experiment management, versioning, and reproducibility using tools like W&B, MLflow, or similar.
Solid understanding of data engineering and cloud infrastructure for ML workloads.
Ability to take ambiguous ideas to production in a fast-paced startup environment.
You’ll Thrive Here If You… (Preferred)
Experience with reinforcement learning, self-evaluating or self-correcting agents.
Publications or patents.
Experience with model compression/optimization (quantization, distillation).
Familiarity with safety evaluation, alignment techniques, and responsible AI practices.
What You’ll Get
A path-defining role in a high-upside company backed by world-class investors
Deep ownership and equity
A team that cares deeply about what we’re building and the people we build it with
A rare chance to leave your mark on something that has the opportunity to become generational
