Machine Learning Engineer

Machine Learning and simulation engineer

Maersk, the world’s largest shipping company responsible for moving 20 % of global trade, is on a mission to become the Global Integrator of Container Logistics. To achieve this, we are transforming into an industrial digital giant by combining our assets across air, land, ocean, and ports with our growing portfolio of digital assets to connect and simplify our customer’s supply chain through global end-to-end solutions, all the while rethinking the way we engage with customers and partners.

In this role as ML and simulation engineer on the Global Data and Analytics (GDA) team, you will be working on our new strategic visibility initiative to develop advanced simulation and optimization solutions for emissions. The overall objective is to further evolve our existing Emissions Studio product (https://www.maersk.com/digital-solutions/emissions-dashboard) with scenario analysis, and AI/ML-powered emissions optimization, which will unlock significant value to our customers as they look to make informed tradeoff decisions on emissions reductions while understanding the impact to transportation time and cost. Building on top of an existing product with an existing customer base, you will be partnering with product managers and engineering counterparts to develop scalable solutions following industry best-practices. You will be empowered to take ownership of your domain and we expect you to proactively contribute to identifying opportunities and solutions. There is a lot of exciting challenges ahead of us, and the ideal candidate will have a passion for working on industry-transforming products and creating impact from the ground up in a fast-paced environment.

To deliver on this scope, we are looking for a candidate with strong problem solving skills with demonstrated hands-on experience in machine learning and scenario simulation. It would be ideal if you are also familiar with mathematical optimization (constrained optimization leveraging techniques from Operations Research such as linear programming), but this is not a must. You should furthermore have experience taking solutions to production in collaboration with colleagues from data engineering and software engineering.

No prior knowledge of logistics needed; we will help you learn what you’ll need to succeed.

Key responsibilities

• Develop, test, and deploy technical solutions for forecasting, prediction, scenario simulation and optimization, as well as other analytical tools together with the team. In addition to the topics mentioned above, this can also include building integrated data sets, analyses and dashboarding
• Lead model development, implementation and deployment end-to-end incl. MLOps (mindset and technical implementation using our stack). Specifically, you will drive problem formulation, modeling approach, implementation, testing, deployment and monitoring. 
• Collaborate with software engineers and data engineers to deploy recommendation solutions to production
• Partner with product managers to drive maturation of ideas into production solutions, including challenging problem formulation
• Communicate effectively with technical and non-technical audiences

Basic qualifications

• BSc/MSc/PhD in computer science, data science or related discipline with 5+ years of industry experience building cloud-based ML solutions for production at scale, including solution architecture and solution design experience
• Good problem solving skills, for both technical and non-technical domains
• Good broad understanding of ML and statistics covering standard ML for regression and classification, forecasting and time-series modeling, deep learning.
• 3+ years of hands-on experience building ML solutions in Python, incl knowledge of common python data science libraries (e.g. scikit-learn, PyTorch, etc)
• Hands-on experience building end-to-end data products based on AI/ML technologies
• Some experience with scenario simulations.
• Experience with collaborative development workflow: version control (we use github), code reviews, DevOps (incl automated testing), CI/CD
• Team player, eager to collaborate and good collaborator

Preferred qualifications

In addition to basic qualifications, would be great if you have…

• Hands-on experience with common OR solvers such as Gurobi
• Experience with a common dashboarding technology (we use PowerBI) or web-based frontend such as Dash, Streamlit, etc.
• Experience working in cross-functional product engineering teams following agile development methodologies (scrum/Kanban/…)
• Experience with Spark and distributed computing
• Strong hands-on experience with MLOps solutions, including open source solutions. 
• Experience with cloud-based orchestration technologies, e.g. Airflow, KubeFlow, etc
• Experience with containerization (Kubernetes & Docker)

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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