Senior Applied Research Engineer - Optimisation, Simulation & ML
Hamburg - Permanent Employee, Full-Time, Hybrid (Monday & Friday remote)
€80,000 - €110,000 + Holiday + Flexible working hours
Excellent opportunity for a Senior Applied Research Engineer to join an innovative start-up that is using data and AI to optimise the product planning and scheduling solutions for process manufacturing.
This company uses technology and real-time data to create a planning system that increases client's profitability and efficiency. Their goal is to build the leading planning solution in process manufacturing, using data as a driving force. They use a state-of-the-art software that is self-service and enterprise ready, delivering feature increments and permanent bug solutions.
You will spearhead the development of core logic and advanced algorithms within the AI & Optimisation Team, directly influencing the efficiency of global supply chains. Operating at the functional heart of the application, your daily work involves navigating a hybrid backend environment that utilises constraint programming, machine learning, and adaptive heuristics. You will be expected to draft technical designs independently and collaborate with a dedicated Full Stack team that manages the heavy lifting of implementation and integration.
The ideal candidate is a seasoned technical professional who possesses the confidence to create robust first drafts without the need for dedicated architects. Beyond technical proficiency, you should have a genuine passion for solving non-linear mathematical problems and a drive to build scalable, generic solutions within a complex and rapidly evolving industrial domain.
This is a fantastic opportunity to join a company in an exciting period of growth where your expertise will contribute to theevolution of data strategy.
The role:
- Develop high-speed, rule-based search algorithms.
- Build custom mathematical solvers using Google OR-Tools.
- Maintain the engine used for solution and schedule testing.
- Design graph-based models to represent complex system states.
- Optimise solver parameters and logic for better performance.
The Person:
- Expert experience with Python
- Strong experience with Go or Rust
- Hands-on experience in end-to-end project delivery (development to operations)
- Mathematical understanding of optimization for scheduling problems
Applied Scientist | ML Innovation Engineer | Machine Learning Engineer | AI Engineer | Algorithm Developer | Deep Learning Engineer | R&D Systems Architect | Agentic Systems Researcher | LLM Optimisation Engineer
Rise Technical Recruitment Limited is acting as an Employment Agency in relation to this vacancy.