Machine Learning Engineer

HEGSØ Search & Consulting has the task of finding a skilled Machine Learning Engineer for our client, the leading subsea technology and development company Teledyne RESON.

Job Purpose:Turn noisy, real-time sensor data into robust machine-learning solutions.

As Machine Learning Engineer you join a multidisciplinary engineering team developing ML for target detection, sonar imaging and pattern recognition in streaming acoustic data. Your work will connect sensors, signal processing, high-performance computing and the information ultimately presented to users.

The sensor systems generate large volumes of real-time data, which is transformed into software products for visualization, post-processing and analysis. The processing chain combines demanding real-time computation with FPGA, DSP and GPU hardware.

You will help develop both the ML models and the infrastructure around them. Because the ML infrastructure supports internal development and customer on-site use, robustness, efficiency and control are central to the role. You will work with industry-standard tools as well as in-house technology.

This is a rare opportunity to apply machine learning to difficult, meaningful data alongside maritime domain experts, software engineers, mathematical modelling engineers and embedded-processing specialists.

What makes the role distinctive:

• Challenging data – find structures and patterns in noisy streaming acoustic and hydrophone data

• End-to-end impact – work from sensor input and model development through to information presented to the user

• Industrial ML – turn novel ML technology into robust, efficient products for internal and customer use

Key Responsibilities:

• Develop machine-learning and data-science solutions for target detection in sonar acoustic data and imaging systems

• Identify structures and patterns in data from hydrophones

• Develop ML models and contribute to the ML infrastructure used in the software products

• Be an active member of a development team spanning software, mathematical modelling and dedicated embedded-processing hardware

• Communicate concepts across the development chain, from sensor input to the final information presented to the user

• Propose improvements to ML models and infrastructure

• Help bring novel ML technologies into robust, industrialized products

• Keep current with relevant technologies and tools

Essential skills:

• Experience with general machine-learning technologies, modern modelling techniques and deep-learning frameworks – PyTorch, TensorFlow or similar