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ML Research Engineer Robotics(m/w/x)
Building ML components for perception and prediction on robotic platforms. Robotics-adjacent ML experience required. 100 EUR net monthly bonus, rooftop terrace.
Requirements
- Strong experience in robotics-adjacent domains (simulation research, generative modeling, multimodal ML)
- End-to-end ML system building
- Solid engineering instincts
- Clean Python coding
- Ability to work with complex, noisy, real-world data
- Deep ML experience in video modeling, generative models, sequence modeling, world models, RL, or simulation-based learning
- Strong software engineering ability
- Writing clean, modular Python
- Building ML systems end-to-end from scratch
- Implementing architectures, training loops, and data pipelines from scratch
- Real-world ML mindset
- Experience with noisy, multimodal, temporal, or large-scale datasets
- Engineering maturity
- Ability to debug, profile, optimize, and scale ML systems beyond prototype
- PyTorch expertise
- Hands-on experience with training pipelines, distributed workloads, or deployment workflows
- Multimodal intuition
- Combining signals such as vision, pose, audio, force/tactile, or simulation state
- Systems sense
- Familiarity with streaming architectures, real-time constraints, microservices, or serialization formats (e.g., Protobuf / MCAP)
- Embodied-AI curiosity
- Interest in teleoperation interfaces, robot interaction, or real-world control dynamics
- Simulation experience
- Knowledge of Isaac Sim, MuJoCo, Unity, Unreal, or related simulation platforms
Tasks
- Build ML components for perception, prediction, or policy pathways
- Develop video models, multimodal encoders, world models, and diffusion/transformer architectures
- Integrate ML pipelines with real-time constraints on robotic platforms
- Work with real datasets for ML systems
- Process multimodal data including video, teleoperation, proprioception, and tactile signals
- Utilize simulation-generated sequences as input
- Test models in realistic environments
- Analyze model failure modes
- Refine models for stability, drift, latency, and robustness
- Collaborate with modeling teams
- Partner with robotics teams
- Work with teleoperation teams
- Engage with simulation teams
- Coordinate with data systems teams
Work Experience
- 5 - 7 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- Isaac Sim
- MuJoCo
- Unity
- Unreal
- Protobuf
- MCAP
Benefits
Corporate Discounts
- Corporate benefits program
Additional Allowances
- 100 EUR net per month
Modern Office
- Modern office facilities
Startup Environment
- Rooftop terrace
Snacks & Drinks
- Free drinks
- Free fruits
Team Events
- Regular company events
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ML Research Engineer Robotics(m/w/x)
Building ML components for perception and prediction on robotic platforms. Robotics-adjacent ML experience required. 100 EUR net monthly bonus, rooftop terrace.
Requirements
- Strong experience in robotics-adjacent domains (simulation research, generative modeling, multimodal ML)
- End-to-end ML system building
- Solid engineering instincts
- Clean Python coding
- Ability to work with complex, noisy, real-world data
- Deep ML experience in video modeling, generative models, sequence modeling, world models, RL, or simulation-based learning
- Strong software engineering ability
- Writing clean, modular Python
- Building ML systems end-to-end from scratch
- Implementing architectures, training loops, and data pipelines from scratch
- Real-world ML mindset
- Experience with noisy, multimodal, temporal, or large-scale datasets
- Engineering maturity
- Ability to debug, profile, optimize, and scale ML systems beyond prototype
- PyTorch expertise
- Hands-on experience with training pipelines, distributed workloads, or deployment workflows
- Multimodal intuition
- Combining signals such as vision, pose, audio, force/tactile, or simulation state
- Systems sense
- Familiarity with streaming architectures, real-time constraints, microservices, or serialization formats (e.g., Protobuf / MCAP)
- Embodied-AI curiosity
- Interest in teleoperation interfaces, robot interaction, or real-world control dynamics
- Simulation experience
- Knowledge of Isaac Sim, MuJoCo, Unity, Unreal, or related simulation platforms
Tasks
- Build ML components for perception, prediction, or policy pathways
- Develop video models, multimodal encoders, world models, and diffusion/transformer architectures
- Integrate ML pipelines with real-time constraints on robotic platforms
- Work with real datasets for ML systems
- Process multimodal data including video, teleoperation, proprioception, and tactile signals
- Utilize simulation-generated sequences as input
- Test models in realistic environments
- Analyze model failure modes
- Refine models for stability, drift, latency, and robustness
- Collaborate with modeling teams
- Partner with robotics teams
- Work with teleoperation teams
- Engage with simulation teams
- Coordinate with data systems teams
Work Experience
- 5 - 7 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- Isaac Sim
- MuJoCo
- Unity
- Unreal
- Protobuf
- MCAP
Benefits
Corporate Discounts
- Corporate benefits program
Additional Allowances
- 100 EUR net per month
Modern Office
- Modern office facilities
Startup Environment
- Rooftop terrace
Snacks & Drinks
- Free drinks
- Free fruits
Team Events
- Regular company events
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Agile Robots
Industry
Engineering
Description
The company develops systems that combine force-moment-sensing and image-processing technology for robotic solutions.
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