We Offer
Joining Maersk, you will become part of the global family of the company that moves 20% of global trade every day all the way, where one of our core values is Our Employees. It goes without saying that we value diversity in all its forms, including but not limited to: gender, age, nationality, race, sexual orientation, disability or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high performing teams.
Key Responsibilities:
- Partner with business, product, and engineering teams to define problem statements, evaluate feasibility, and design AI/ML-driven solutions that deliver measurable business value.
- Lead and execute end-to-end AI/ML projects — from data exploration and model development to validation, deployment, and monitoring in production.
- Drive solution architecture using techniques in data engineering, programming, machine learning, NLP, and Generative AI.
- Champion the scalability, reproducibility, and sustainability of AI solutions by establishing best practices in model development, CI/CD, and performance tracking.
- Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews.
- Identify and evangelize the adoption of emerging tools, technologies, and methodologies across teams.
- Translate technical outputs into actionable insights for business stakeholders through storytelling, data visualizations, and stakeholder engagement.
Who We are Looking for:
- A seasoned AI/ML scientist with 2-6 years of hands-on experience delivering enterprise-grade AI/ML solutions.
- Advanced proficiency in Python, SQL, and experience working with cloud platforms (Azure preferred) and tools such as ADF, Function Apps and Web Apps.
- Strong expertise in applied text analytics, NLP, and Generative AI, with real-world deployment exposure.
- Solid understanding of model evaluation, optimization, bias mitigation, and monitoring in production.
- A problem solver with scientific rigor, strong business acumen, and the ability to bridge the gap between data and decisions.
- Prior experience in leading cross-functional AI initiatives or collaborating with engineering teams to deploy ML pipelines.
- Bachelor's or master’s degree in computer science, Engineering, Statistics, or a related quantitative field. A PhD is a plus.
- Prior understanding in business domain of shipping and logistics is an advantage.