Principal Software Engineer (f/m/d) - Lab Automation
- Compensation
- Not disclosed
- Location
- Penzberg
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Software engineering
- Posted
Skills
Must have
- A study degree in Computer Science or a similar technical field, or equivalent practical experience, and substantial (ideally 8+ years) professional experience.
- Practical exposure working in a biotech or pharmaceutical research environment.
- Strong passion for software engineering with expert-level proficiency in Python and/or Typescript, and deep expertise in cloud-native architectures (ideally AWS/GCP), RESTful APIs, microservices, serv
- Experience in at least two protocols/technologies such as NATS, Kafka, MQTT, or GraphQL.
- A strong opinion on how the team can adopt AI coding workflows to deliver higher-quality code faster than was possible in the pre-agentic era, using AI tools heavily as foundational software platforms
- You've owned or significantly shaped a technical roadmap, made the call on what to build, defer, and decommission, and you make pragmatic tradeoffs.
- A skilled communicator capable of building trusted partnerships with scientists and defining high-level technical architecture for complex work.
- Preferred but not required: Experience in training, evaluating, or adopting AI/ML models (including reinforcement or imitation learning for robotics) and capable of building and evaluating AI-enabled
Full description
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
The Position
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche.
Your Opportunity
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients Worldwide.
Within the CoE organisation, the Data and Digital Catalyst (DDC) organisation drives the modernisation of our computational and data ecosystems and integration of digital technologies across Research and Early Development to enable our stakeholders, power data-driven science and accelerate decision-making.
As a Principal Software Engineer (fm/d), you will be a key contributor to the architecture and delivery of automation systems for drug discovery. You will work with a team of software-focused engineers to bring the software and hardware layers into production. You will empower our scientists with robust, error-resilient and well monitored systems.
Your Key Responsibilities:
- Architecture & Development: Build software that controls lab instruments (e.g., liquid handlers, plate readers, robot arms) and develop instrument drivers and APIs using different protocols (e.g., serial, USB, TCP/IP).
- System Integration: Lead the development of drivers, APIs, and middleware to seamlessly connect custom and commercial robotic platforms with LIMS and ELNs.
- Agentic Systems & Digital Twins: Build agentic systems and digital representations of labs to execute scientific experiments for drug discovery, reasoning over factors such as sample identity, instrument state, and resource availability.