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Machine Learning Engineer – Autonomous Perception & AI Systems

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Summary

Machine Learning Engineer in Stockholm or Gothenburg building multi-modal perception and autonomy systems: designing and training models for sensor fusion, 3D detection, tracking, and scene understanding, then deploying them on NVIDIA edge hardware using PyTorch, CUDA/TensorRT, ROS2, and robotics foundation models.

We are looking for a highly skilled Machine Learning Engineer with a passion for building next-generation multi-modal perception and autonomy systems. You will join a team developing advanced AI capabilities for autonomous platforms, leveraging state-of-the-art technologies in computer vision, sensor fusion, robotics, and foundation models.

The ideal candidate combines strong software engineering capabilities with hands-on machine learning expertise and has experience taking innovative R&D concepts from prototype to deployment in mission-critical environments.

Your Responsibilities

  • Design, train, and optimize advanced ML/DL solutions for:

    • Multi-modal sensor fusion

    • 3D object detection and classification

    • Scene understanding and semantic segmentation

    • Object tracking and trajectory prediction

    • Behavior modeling and autonomous decision support

  • Develop and maintain scalable data and training pipelines, including:

    • Data curation and labeling

    • Synthetic data generation

    • Data augmentation and evaluation

    • Continuous model monitoring and performance optimization

  • Work with cutting-edge AI architectures, including:

    • Vision-Language-Action (VLA) models

    • Foundation models for robotics and autonomy

    • Reinforcement Learning (RL) and imitation learning approaches

    • Multi-modal transformer-based architectures

  • Integrate and optimize models for deployment on embedded and edge computing platforms, utilizing technologies such as:

    • NVIDIA GPU acceleration

    • CUDA and TensorRT

    • NVIDIA Jetson platforms

    • High-performance inference frameworks for real-time execution

  • Ensure accurate sensor calibration, alignment, and synchronization across complex sensor suites, mitigating drift and environmental disturbances encountered in operational environments.

  • Collaborate closely with Systems Engineering, Planning, Controls, Robotics, and Software teams to develop safe, reliable, and deployable autonomous systems.

  • Investigate and evaluate emerging technologies such as Alpamayo-based robotics frameworks, next-generation autonomy stacks, embodied AI, and autonomous agent architectures.

We Are Looking For

  • 3–5+ years of experience in Machine Learning, Robotics, Computer Vision, Artificial Intelligence, Applied Mathematics, Computer Science, or a related field.

  • Strong practical experience with:

    • PyTorch and/or TensorFlow

    • End-to-end model development and deployment

    • Training, evaluation, optimization, and productionization of ML systems

  • Experience in one or several of the following areas:

    • Computer vision

    • Autonomous systems

    • Robotics

    • Multi-sensor perception

    • Reinforcement Learning (RL)

    • Vision-Language Models (VLM)

    • Vision-Language-Action (VLA) systems

  • Familiarity with modern AI and robotics ecosystems such as:

    • NVIDIA Isaac Sim / Isaac Lab

    • ROS2

    • Alpamayo

    • CUDA/TensorRT

    • Synthetic data and simulation environments

  • Strong background in:

    • Linear algebra

    • Probability and estimation theory

    • Optimization

    • Algorithm design

    • Data structures and software architecture

  • Experience developing in:

    • Python

    • C/C++

  • Ability to obtain and maintain a security clearance.

Personal Qualities

We believe you are a curious and hands-on engineer who enjoys solving difficult technical challenges and continuously exploring new technologies. A strong self-driven mindset, demonstrated through personal projects within AI, robotics, autonomous systems, or software development, is highly valued.

Bonus Qualifications

  • Experience developing embodied AI or autonomous robotics solutions.

  • Experience with large-scale foundation models and generative AI.

  • Knowledge of imitation learning, world models, or agentic AI systems.

  • Experience deploying ML workloads on NVIDIA edge hardware.

  • Contributions to open-source robotics or machine learning projects.

Location: Stockholm or Gothenburg

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