Hybrid ML Engineer for Autonomous Perception & Planning

Spline

Kraków

Hybrid

PLN 180,000 - 280,000

Part time

14 days+

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Job summary

Spline is seeking a Machine Learning Engineer to develop intelligent perception and decision-making for autonomous systems. You will build ML models for computer vision, sensor data processing, motion prediction, and automated planning, with real-world validation and cross-team collaboration.

Responsibilities include training pipelines, evaluation, and improving tools and workflows across perception and prediction tasks. You will work in Kraków on a hybrid model with data-focused projects.

Qualifications

  • Master’s degree in a technical field.
  • Hands-on ML and CV experience with modern frameworks.
  • Strong Python programming and English skills.

Responsibilities

  • Develop, train, and optimize ML models for perception and prediction.
  • Work on object detection, segmentation, tracking, and 3D understanding.
  • Integrate data from multiple sensors and modalities.
  • Support trajectory prediction and planning algorithms.
  • Build data pipelines for training and evaluation.
  • Analyze model accuracy, robustness, and performance on large datasets.
  • Validate algorithms in real-world scenarios and collaborate with teams.
  • Improve tools, models, and engineering processes.

Skills

Python
Computer Vision
Deep Learning
English Proficiency
ML Model Training

Education

MSc in Computer Science, Machine Learning, Robotics, Computer Vision, or related field

Tools

PyTorch
TensorFlow
Model Evaluation

Job description

Spline is seeking a Machine Learning Engineer to develop intelligent perception and decision-making for autonomous systems. You will build ML models for computer vision, sensor data processing, motion prediction, and automated planning, with real-world validation and cross-team collaboration.

Responsibilities include training pipelines, evaluation, and improving tools and workflows across perception and prediction tasks. You will work in Kraków on a hybrid model with data-focused projects.

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