Machine Learning Engineer

Phantasma Labs GmbH; Berlin; Hybrid; EUR 85,000 - 120,000; Full time

Job summary

Phantasma Labs GmbH in Berlin is seeking a Machine Learning Engineer to work on the AI powering AiPS, our production scheduling software. You will develop reinforcement learning agents and Digital Twin environments to model real factory problems.

You'll own approaches, collaborate with engineering teams and customers, and translate requirements into scalable features that run in production.

Qualifications

• 5+ years of Python experience.
• 2+ years in factory shopfloor operations or 2+ years with ERP/MES systems.
• Strong understanding of manufacturing processes and RL basics.
• Experience applying reinforcement learning to real-world problems.

Responsibilities

• Develop and improve reinforcement learning models and simulation environments.
• Write robust Python code, perform reviews and mentorship.
• Create unit and integration tests with unittest/pytest.
• Collaborate with ML specialists and software engineers to deliver production-grade systems.
• Engage with customers to translate requirements into technical features.

Skills

Python

Reinforcement learning basics

Education

Background in Computer Engineering, Mathematics, Machine Learning, Industrial Engineering or related field

Tools

PyTorch

Optuna

MLflow

Job description

As a Machine Learning Engineer at Phantasma, you'll work on the core AI behind AiPS, our production scheduling software. You'll develop and improve our reinforcement learning agents, work on the Digital Twin environments they train in and help turn complex manufacturing problems into models that work in real factories.

You'll have a lot of ownership over how we approach these problems and work closely with both our engineering team and customers.

Tasks

You'll work on the development and improvement of our reinforcement learning models and simulation environments:

• Write robust, scalable and production-ready Python code
• Provide code reviews, guidance and mentorship to fellow developers to maintain high coding standards
• Write unit and integration tests using tools such as unittest and pytest
• Design, engineer and optimize features in the Digital Twin for reinforcement learning simulations using Python, NumPy and Pandas
• Create, optimize and maintain training and evaluation scripts for RL agents
• Set up and maintain Python environments using modern tools such as uv and conda
• Work collaboratively using Git and GitHub
• Participate in customer calls to understand requirements and translate them into actionable technical features
• Brainstorm and develop ideas to improve the RL agent, including algorithms, reward functions and architecture

Requirements

We're looking for someone who combines strong Python experience with an understanding of manufacturing environments and an interest in applying reinforcement learning to real-world production challenges.

Must Haves:

• Background in Computer Engineering, Mathematics, Machine Learning, Industrial Engineering or a related field
• 5+ years of Python experience
• 2+ years of experience in factory shopfloor operations as an engineer or planner, or 2+ years of experience with ERP/MES systems for factories
• Strong understanding of manufacturing processes across different environments, including discrete manufacturing, line production and engineer-to-order
• Basic understanding of reinforcement learning and experience developing or applying RL algorithms

Nice to Haves:

• 3+ years of experience in factory shopfloor operations as an engineer or planner, or 3+ years of experience with ERP/MES systems for factories
• Research experience developing RL algorithms
• Experience with CI/CD pipelines, particularly GitHub Actions
• Experience using libraries and tools such as PyTorch, Optuna and MLflow
• Ownership from day 1: Work in a small team with fast feedback and see the impact of what you build
• Collaborate with a strong team: Work alongside ML specialists developing our AI optimization technology and software engineers building the production‑grade systems around it
• A supportive, open culture: Clear communication, strong collaboration and flat hierarchies
• Flexible working hours & hybrid setup: Work remotely or from our co‑working space in Berlin Mitte, whatever helps you do your best work
• Company laptop: We’ll provide the equipment you need to do your work