Senior Machine Learning Engineer

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