Machine Learning Senior Engineer

Overview

Develop and deploy ML models for autonomous vehicle perception on embedded hardware.

Key Responsibilities

• model optimization
• embedded software
• ml requirements
• data handling
• model training
• project leadership

Tasks

-Optimize models for embedded hardware and develop software to run models on embedded hardware and communicate with the rest the hardware on a machine. -Derive machine learning and data requirements; -Work with large datasets to develop, train, and test machine learning models; -Lead and contribute to projects throughout the whole development cycle;

Requirements

• ros/ros2
• lidar
• nvidia
• c++/python
• opencv
• master's

What You Bring

-2 years experience with ROS/ROS2, with LiDAR, RGB cameras and stereo cameras along with fusing data from multiple sensors together, and with data engineering, such as organizing and managing large datasets and using Azure storage; Nvidia Jetpack and Nvidia tool chains such as DeepStream; optimizing and deploying perception models on Nvidia based embedded hardware; and leading a Machine Learning project, including determining project scope, goals, tasks to complete, timeline estimates and delegating/managing tasks completion through others -Master’s degree in Computer Science, Data Science, or Robotics. -4 years experience coding in C++ and/or Python and with Computer Vision and Machine Learning frameworks such as OpenCV, TensorFlow, PyTorch.

People Also Searched For

Benefits

-We promote from within and support your learning with mentoring, training, and access to global opportunities. -You’ll have flexibility, autonomy, and support to do your best work while maintaining a healthy work-life balance. Your well-being matters to us. -You’ll receive benefits like 13th salary, annual bonus, paid vacation, pension plans, personal insurance, and more. These vary by country and contract, but they’re worth asking about—we think they’re pretty great.

About Danfoss

-Begun in 1933 with a novel refrigeration valve and soon introduced thermostatic radiator valves, driving early energy-efficiency innovation. -Expanded into hydraulics, power electronics, and sensor systems, launching the first VLT frequency converter in 1968 and acquiring notable divisions such as Vacon and Eaton Hydraulics. -Typical projects range from district-energy systems and marine/offshore equipment to EV drivetrain modules, industrial automation, and large-scale cold-chain refrigeration. -Expertise spans HVAC, mobile & industrial hydraulics, AC drives & power electronics, high-pressure pumps, sensing/control components, and fire-safety systems.

Sector Specialisms