AI Modeling Lead | DeepSea Technologies · Teeming.ai
DeepSea Technologies
DeepSea harnesses the latest in AI technology to make ships more efficient. Bringing together experts from technology and maritime, DeepSea focuses on increasing the efficiency and decreasing the fuel consumption of vessels through a combination of technical and operational insights powered by detailed AI-generated performance models. We work with forward-thinking shipping companies to make the shipping industry leaner, greener and better connected.
DeepSea harnesses the latest in AI technology to make ships more efficient. Bringing together experts from technology and maritime, DeepSea focuses on increasing the efficiency and decreasing the fuel consumption of vessels through a combination of technical and operational insights powered by detailed AI-generated performance models. We work with forward-thinking shipping companies to make the shipping industry leaner, greener and better connected.
ETF (Environmental Technology Fund) investment announced Jan 20, 2021 for M (reporting indicates 2020 as the year attributed to the investment)
- 2021-07-29
,000,000
M round reported 29 July 2021 with participation from The Signal Group and ETF Partners
- 2023-07-18
Nabtesco became the primary shareholder in July 2023 (acquisition/majority stake)
Investor Signal
“Includes sector-focused investors (ETF Partners, Nabtesco Technology Ventures, The Signal Group) and acquisition/majority stake by Nabtesco Corporation”
Founders
What we do
Join the Team
AI Modeling Lead
On-SiteAttiki, GR
On-Site • Attiki, GR
About Us
DeepSea is a maritime technology leader, providing a unified optimisation platform that helps shipping companies cut fuel consumption, reduce emissions, and transform vessel performance across entire fleets.
Built on the most advanced maritime AI data pool in the world, DeepSea’s platform powers everything from vessel monitoring to advanced automation - helping clients achieve measurable results with clarity, speed and scale.
We are trusted by some of the world’s most forward-thinking ship owners and operators, and our team spans Greece, the UK, Armenia, Romania, and Japan. As the shipping industry undergoes enormous change, we are at the centre of that transition - helping our customers take control, reduce risk, and build competitive advantage.
Main Responsibilities
Manage and own the end-to-end delivery of production AI solutions, from data/model/software requirements gathering and analysis, to model design and development, to model validation and deployment to our products.
Lead the development of AI models for our products and customers, in the field of vessel modelling and beyond, identify emerging trends and technologies in AI, explore new R&D areas, and drive innovation in the field in close collaboration with the company’s CTO.
Lead a team of data scientists, machine learning engineers, software engineers, MLOps engineers and naval experts, provide guidance and mentorship, and set R&D priorities.
Main Requirements
Nice to Have
Experience in applying ML/AI techniques in the maritime domain, particularly for vessel modelling, condition monitoring, and predictive maintenance, will be considered a strong asset.
A solid publication track record and ability to present complex AI concepts to both technical and non-technical audiences.
What we offer
:
You will be part of a dynamic team focused on delivering results and continuous improvement while disrupting the industry, and will also receive:
Competitive remuneration package: Skill & experience-based salary and eligibility for additional employee benefits.
Health Package: Private health insurance coverage and mental health - therapist benefit
Paid leaves: emergency and medical leaves.
Learning and Development Package: Access to courses platform and eligibility for seminars, conferences and workshops
Remote Flexibility: Great office space in the heart of Athens with hybrid option.
At DeepSea, we are looking for people who share our values and are aligned with our mission. It is important to us to ensure that no-one who is eager and capable of contributing constructively to our team is excluded because of ethnic or social origin, gender or sexuality, age or family status, disability or medical conditions etc. Diversity is well-proven to be a vital characteristic of teams that succeed, so we do everything we can to make our environment welcoming and safe for everyone.
Data Privacy
The company ensures that the personal data of candidates is handled with care and in compliance with GDPR regulations. Your personal data will be stored securely and only for the duration necessary under the law. If the recruitment process is unsuccessful, your data will be retained for 5 (five) years to consider you for future opportunities. After this period, your data will be deleted or destroyed. In case you do not wish for the company to keep your CV and personal data, please send an email to dpo@deepsea.ai.
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Communicate and collaborate with both internal stakeholders and customers to understand business needs and requirements and present complex concepts to non-technical audiences.
Work seamlessly in a complex cross-disciplinary environment and deliver solutions to our customers on time.
Facilitate a culture of peer review and constructive feedback to enhance the quality of R&D outputs.
Identify and recruit top talent in the field of AI Modelling, and integrate them into the team.
Bachelor’s degree in Engineering, Mathematics, Physics, Computer Science or related field.
PhD (preferred) or Master's in Machine Learning, Data Science, Engineering, Applied Mathematics or related field.
Proven expertise in designing, developing and rolling out production AI models, particularly for regression problems.
Proven expertise in data preprocessing and feature engineering.
Proven expertise in Machine Learning, Deep Learning, Neural Networks, Recurrent Neural Networks, Decision Trees, Boosting and Autoencoders. Candidates with proven expertise in Physics-Informed Neural Networks, Convolutional Neural Networks, Attention Mechanisms, Transformers, Large Language Models and Hybrid Architectures will also be considered.
Proven experience in leading AI projects end-to-end, including requirements gathering and analysis regarding data, models and software, evaluation framework design, model design and development, and model validation and deployment.
Proven experience in leading multidisciplinary teams of data scientists, machine learning engineers, software engineers, MLOps engineers, etc., providing guidance, mentorship, and setting R&D priorities.
Experience with data engineering, data warehouses and lakehouses, ETL/ELT data integration, and modern data platforms such as Databricks or similar.
Programming skills in Python with Pytorch, Keras, Tensorflow, Pandas, NumPy, SciPy, scikit-learn or similar frameworks.
Familiarity with MLOps practices, pipeline automation, model versioning, model CI/CD, and model serving using MLflow, W&B, Airflow, Jenkins or similar tools and frameworks.
Strong communication and collaboration skills in an agile, dynamic and cross-disciplinary environment.
