Maritime Machine Learning Engineer, Teledyne Marine product lines
HEGSØ Search & Consulting has the task of finding a skilled person within Machine Learning, for our client, leading subsea technology and development company, Teledyne RESON Marine.
As a Machine Learning Engineer in the team, you will be exposed to a broad range of technical topics.
Sensor systems produce massive amounts of real-time data, and we perform massive computations of data to reach the data products ready for UI rendering, post processing and information analysis.
Data throughput happens at full speed, so highly efficient computations, and hardware optimized programming is performed in our software.
We execute our end-user software mostly on the Windows platform, but making our source code platform agnostic.
You will have a challenging and interesting job, producing products for real tough applications and interesting customers globally.
The ideal candidate has deep understanding of ML and the ability to influence senior business and technology leaders in laying out the roadmap for AI and ML infrastructure and models. The solutions developed will encompass analysis, development, deployment of statistical based ML and deep learning models.
If your interests are in technical products and high-performance computing, we offer a rare and unique opportunity to join a team of maritime domain experts with great passion for building products.
- Maritime ML engineer with specific product domains as primary responsibility, that will be “yours” to manage
- Active part of the team, also with the software and hardware engineers throughout projects related to data acquisitions, up/downstream communication, how to manage massive data throughput through hardware and software
- Develop ML models and work on the ML infrastructure of our software products
- Communicate concepts and maintain dialogue with the rest of the development team, from sensors input to the final information presented to the user
- Ensure ML models meets all requirements of quality, security, modifiability, extensibility etc.
- Evaluate and communicate potential ML model or infrastructure improvements
- Propose improvements in ML models or infrastructure
- Keep up with the latest technology and tools, keep the ML engineering level standards high
- ML engineering experience: highly skilled
- Deep learning techniques and how to apply them
- Proficient in programming language, Python or equal
- Knowledge of modern ML modelling techniques, ML models and applied models
- Expert level knowledge of PyTorch architecture and components
- Understanding of software quality assurance principles and build tools
- A technical mindset with great attention to detail
- Able to drive smaller projects from start to finish
- In larger projects spanning many man-years of effort, work as a Team player with strong problem-solving ability and a can-do mentality, dividing the workload between peers
- Good communication skills on technical level, ability to work with distance distributed teams, ability to participate in customer meetings for integration support from time to time (engineers to engineers)
- Proficient in English language
Qualifications & Experience:
- M.Sc., ML engineering or similar
- Experience with relevant comparable software design
Behavioural Competencies/Physical requirements:
- Able to work in a global team, we are working distributed between countries
- Good communicator with development team members
- Take ownership and responsibility, deliver to agreements and keep promises
- Enthusiastic ‘can-do’ attitude, energetic
- Idea generator, makes connections, original thinking
- Interested and engaged with new technologies and industry challenges
- Interest in the products, user cases, marine domain, customers
Job location Copenhagen, Denmark is preferred due to the team-effort taking place between the ML and software engineers. We may consider alternatives for a special candidate.
If you want to know more, please contact:
Anders Hegelskov, HEGSØ Search & Consulting, Phone: +45 3035 6405 – Mail: email@example.com