Expert Deep Learning Engineer (Autonomous Driving)

Department/Project Description:

Our client is dedicated to making safe, intelligent mobility a reality. Headquartered in Sweden, they develop a complete, scalable software stack for ADAS and autonomous driving - from sensing to actuation - and are soon to launch with a major global automaker.

Driven by the goal of reducing fatal accidents by 100%, their team of 500+ global engineers combines technical excellence with a shared passion for saving lives. The company values a T-shaped competence profile, prioritizing a strong mindset, responsibility, and collaboration over a pure skill set. They offer a flexible hybrid work environment where ambition, mentorship, and software craftsmanship thrive.

Job Description:

Defining the "Expert"
To succeed in this role, you must possess:

• Deep knowledge and intuition for spatio-temporal neural networks: You don't just use libraries; you understand the mathematical movement of data through time and space within a network.

• Proven experience in E2E driving: You have a background in the AD/ADAS domain and understand the complexities of End-to-End learning architectures.

   

Technical Skills:

• Deep Learning Mastery: A thorough theoretical and practical understanding of Deep Learning principles.
• Frameworks: Expert-level proficiency in PyTorch or TensorFlow.
• Programming: Advanced Python software development skills (OOP, design patterns, testing).
• Mathematics: Strong foundation in Statistics and Geometry, specifically applied to 3D environments and kinematics.

• Data Engineering: Ability to build and maintain efficient data pipelines for large-scale datasets.

   

Meriting Competencies (Nice-to-Have):

• Experience with Transformers and Multi-head attention mechanisms.
• Background in Recurrent Neural Networks (RNNs) (LSTMs, GRUs) for time-series data.
• Knowledge of Perception modalities, including Computer Vision, LiDAR, and Radar.
• Experience with Object Tracking algorithms in dynamic environments.

Personal Characteristics:

• Problem Solver: You approach undefined and complex challenges with an analytical mindset.
• Active Listener: You value the inputs of others and listen to understand, not just to reply.
• Humble & Respectful: You are a team player who leaves your ego at the door. You mentor others and accept feedback with grace.
• Responsibility: You have a strong sense of ownership of the "greater picture"- optimizing not just for accuracy metrics but also for the product's actual safety and functionality.

Job Responsibilities:

We are looking for an Expert Deep Learning Engineer to lead the development of next-generation autonomous driving systems. This is not a standard engineering role; it is a position for a technical leader who possesses a profound intuition for how neural networks interpret time and space.

As an expert, you will look beyond the code to the greater picture, bridging the gap between theoretical deep learning research and real-world implementation in safety-critical environments.

Key Responsibilities:

• Architectural Design: Design and implement novel Deep Learning models with a focus on spatio-temporal dynamics for autonomous navigation.
• Full-Stack DL Engineering: Manage the lifecycle of the model from data engineering and preprocessing to training, validation, and deployment.
• Mathematical Modeling: Apply advanced statistics and geometry to solve complex perception and path-planning problems.
• Software Excellence: Write robust, production-grade Python code that integrates seamlessly with our broader software stack.
• Big Picture Alignment: Take responsibility for how your models affect the vehicle's overall behavior, ensuring safety and performance goals are met.