AI/ML Engineer - Behavioral Safety (m/f/d)

Synapticon; Schönaich; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Benefits dieser Stelle

Creative freedom

30 days paid vacation

Company pension scheme

Flexible working hours

Gym memberships

Health program

Job bike program

Regular team-building events

Zusammenfassung

Synapticon is seeking an experienced AI/ML Engineer to join our innovative Safety AI team in Schönaich, near Stuttgart. You will focus on developing machine learning systems to enhance safety in humanoid robots, from intent recognition to fall strategies. The ideal candidate has at least 3 years of experience in deploying ML systems in real-time contexts and will help set the technical direction for challenging problems in robotics.

Join us for a fulfilling full-time role with flexible working hours, ample vacation, and the chance to make a significant impact in a collaborative and dynamic work environment.

Qualifikationen

• Minimum 3 years of professional experience in ML systems for safety-relevant domains.
• Experience with integrating ML inference pipelines in real-time.
• Knowledge of system design and engineering best practices.

Aufgaben

• Lead the integration of multimodal models into the safety stack.
• Develop AI-based fall strategy controllers.
• Optimize ML model inference within real-time control loops.
• Establish evaluation frameworks for safety behavior.

Kenntnisse

Machine Learning systems development

Real-time control contexts

ROS2 integration

Code ownership and documentation

Safety-critical AI interest

Linear algebra

Optimization

Probability

Jobbeschreibung

Synapticon builds the motion control and actuator technology at the core of next-generation humanoid robots. Our ACTILINK actuator series and Positron Safety AI architecture are deployed in some of the most demanding humanoid and advanced robotics programmes globally.

Right now we're looking for an experienced AI/ML Engineer (3+ years) to join our Safety AI team in Schönaich (close to Stuttgart). You will own the development and productization of machine learning systems that give humanoid robots semantic awareness and reliable safety behavior — from intent recognition to AI-based fall strategies. This is a role for someone who has shipped ML into real-time, safety-relevant systems and wants to set the technical direction for one of the harder problems in humanoid robotics.

Responsibilities

• Own the integration of multimodal foundation models into our robot safety stack, taking systems from architecture through to production deployment
• Design, build, and productize AI-based fall strategy controllers, driving technical decisions on one of the genuinely open problems in humanoid deployment
• Architect and optimize ML model inference within the real-time robot control loop, balancing model performance against hard timing constraints
• Define benchmarking methodology and lead the evaluation of behavioral safety classifiers for semantic intent recognition across simulation and deployment
• Establish evaluation frameworks for AI safety behavior aligned with ISO/IEC TR 5469, setting standards and best practices the team builds on
• Mentor and review the work of more junior engineers and contribute to the technical roadmap of the Safety AI team

Qualifications

• At least 3 years of professional experience building and deploying ML systems in production, ideally in robotics, autonomous systems, or another safety-relevant domain
• Demonstrated experience integrating ML inference pipelines with ROS2 in real-time control contexts
• Hands‑on experience fine‑tuning and adapting foundation models for specific applications, not just deploying them off the shelf
• A track record of code ownership, sound system design, and engineering best practices (testing, reproducibility, documentation)
• Deep interest in safety‑critical AI as a hard technical and methodological problem, not a compliance checkbox
• Solid mathematical foundation in linear algebra, optimization, and probability

Benefits

• A warm, international team that truly enjoys working together
• Plenty of creative freedom and the opportunity to make a real impact
• Flexible working hours and hybrid work options
• Short decision‑making paths, flat hierarchies, and open communication
• Professional development opportunities and exciting projects
• 30 days of paid vacation
• Full‑time position (40 hours/week) with a permanent contract
• Company pension scheme through Dyno
• Flexible working hours when life takes unexpected turns
• Company‑supported gym memberships through Wellpass
• A company‑sponsored health program (WLP app, regular physical activities, nutritional coaching, and more)
• Job bike program to support a healthy commute (optional)
• Birthday vouchers
• Snacks and fresh fruit for all employees, plus breakfast every Monday
• Free drinks and coffee, of course
• Regular global team‑building events such as bootcamps, ski trips, and summer BBQs — spouses and children are warmly invited to Friday BBQ events
• Modern office spaces