Machine Learning Engineer – Perception & Autonomous Systems

Spline; Kraków; On-site; PLN 180,000 - 240,000; Full time

Job summary

Spline is seeking a Machine Learning Engineer to join a team building perception and decision-making solutions for autonomous systems. You will work on ML algorithms used in computer vision, sensor data processing, motion prediction, and automated planning, with datasets and real-world validation.

You will collaborate with software, systems, and product teams to improve pipelines, models, and engineering processes, in a hybrid Kraków-based role with modern ML tooling.

Qualifications

• MSc in Computer Science, ML, Robotics, CV, or related field.
• Hands-on experience in machine learning, deep learning, or computer vision.
• Strong programming skills in Python.
• Practical knowledge of PyTorch or another modern ML framework.
• Experience with CNNs/Transformers or Vision Transformers; object detection, segmentation, tracking, or 3D perception.

Responsibilities

• Develop, train, and optimize ML models for perception and prediction.
• Work on computer vision tasks: object detection, segmentation, tracking, 3D scene understanding.
• Design solutions combining data from multiple sensors and input modalities.
• Support trajectory prediction and automated planning algorithms.
• Build and maintain data processing, model training, and evaluation pipelines.
• Analyze model accuracy, robustness, and performance on large-scale datasets.
• Validate algorithms in real-world use cases and operating conditions.
• Collaborate with software, systems, and product teams.
• Contribute to tool and process improvements in development workflows.

Skills

Python

PyTorch

Machine learning

Computer vision

Object detection

3D perception

Education

MSc in Computer Science / ML / Robotics / CV

Job description

We are looking for a Machine Learning Engineer to join a team developing intelligent perception and decision-making solutions for autonomous systems.

In this role, you will work on machine learning algorithms used in computer vision, sensor data processing, motion prediction, and automated planning. You will have the opportunity to contribute to solutions operating on complex datasets and validated in real-world scenarios.

Your responsibilities

• Develop, train, and optimize machine learning models for perception and prediction.
• Work on computer vision tasks such as object detection, segmentation, tracking, and 3D scene understanding.
• Design solutions that combine data from multiple sensors and input modalities.
• Support the development of trajectory prediction and automated planning algorithms.
• Build and maintain data processing, model training, and evaluation pipelines.
• Analyze model accuracy, robustness, and performance using large-scale datasets.
• Validate algorithms against real-world use cases and operating conditions.
• Collaborate with software, systems, and product engineering teams.
• Contribute to the continuous improvement of development tools, models, and engineering processes.

Key requirements:

• MSc in Computer Science, Machine Learning, Robotics, Computer Vision, or a related technical field.
• Hands‑on experience in machine learning, deep learning, computer vision, or a similar area.
• Strong programming skills in Python.
• Practical knowledge of PyTorch or another modern machine learning framework.
• Experience in several of the following areas:
  • CNNs, Transformers, or Vision Transformers,
  • object detection, segmentation, tracking, or 3D perception,
  • temporal and sequential modelling,
  • representation learning, self‑supervised learning, or multimodal learning.
• Experience working with datasets, training workflows, and model evaluation.
• Good command of English.

Nice to have

• Experience with trajectory forecasting, motion planning, or reinforcement learning.
• Knowledge of C++.
• Experience with large‑scale model training, optimization, or deployment.
• Knowledge of embedded systems, edge computing, or Edge AI.
• Form of cooperation: Employment contract or B2B (your choice).
• Location: Krakow / hybrid