Job
Description
A.P. Moller Maersk is the global leader in container shipping services, operating in 130 countries and employing approximately 80,000 staff. As an integrated container logistics company, Maersk aims to connect and simplify its customers supply chains. We are at the forefront of digital transformation, leveraging cutting-edge technology to revolutionize global trade. Position Summary: We're looking for a driven Senior Machine Learning Engineer to develop groundbreaking solutions in classical ML, Natural Language Processing (NLP), and Deep Learning, revolutionizing global logistics. As a Senior Engineer, you will work closely with Lead Machine Learning Engineers to spearhead the development and deployment of cutting-edge machine learning models. This role offers a significant opportunity for professional growth, allowing you to expand your skill set while making meaningful contributions to impactful projects that directly shape the future of our industry. Key Responsibilities: Model Development & Deployment: Build and deploy robust machine learning models for predictive and prescriptive analytics, focusing on groundbreaking solutions in classical ML, NLP, and Deep Learning. Feature Engineering & Optimization: Select relevant features, and build and optimize machine learning algorithms that deliver significant impact on business outcomes. Cross-functional Collaboration: Collaborate closely with cross-functional teams to understand complex business requirements and translate them into effective analytical solutions. Performance Monitoring: Define validation frameworks, establish processes to ensure acceptable data quality criteria, and continuously monitor model performance, creating alerts for any data leakage or degradation. Debugging & Reliability: Debug and analyze problems in distributed systems, even addressing issues outside your immediate sphere of technology, with a strong focus on simplicity and reliability. Continuous Learning & Best Practices: Stay updated with the latest developments in data science and machine learning, and actively contribute to implementing best practices within the team. Communication: Clearly and kindly communicate complex concepts, both in written and verbal forms, including presenting findings to diverse stakeholders. Code Quality: Be familiar with Git and actively participate in peer reviews of contributions to ensure high code quality. Required Qualifications (Must Haves): Experience: Proven hands-on experience with machine learning algorithms and libraries (e.g., TensorFlow, Keras, or PyTorch) for tasks like classification, regression, clustering, and natural language processing (NLP). ML Fundamentals: A solid understanding of core machine learning concepts and techniques, including knowledge of deep learning architectures, optimization algorithms, backpropagation, and hyperparameter tuning. System Debugging: Comfort in debugging and analyzing problems within distributed systems, including issues extending beyond your direct area of technology expertise. Software Engineering Principles: A strong penchant for simplicity and reliability in code and system design. Version Control: Familiarity with Git and a willingness to have contributions peer-reviewed. Continuous Improvement: A passion for continuous learning and professional development. Communication: Clear and kind communication skills, both written and verbal. Preferred Qualifications (Good to Have): Observability Domain Knowledge: Understanding of the Observability domain, including context awareness and customizing language models accordingly. Advanced ML Techniques: Exposure to advanced imputation, sophisticated feature engineering, re-training strategies, and hyperparameter tuning. Data Presentation: Experience in visualizing and presenting data effectively for various stakeholders. Big Data Technologies: Understanding of big data technologies (e.g., Hadoop, Spark). Cloud Platforms: Familiarity with cloud platforms and services (e.g., AWS, Azure). Skills: Statistical Data Analysis Data Visualization Data Science Python or R (Programming Language) Data Analytics Understanding of big data technologies (e.g., Hadoop, Spark) Familiarity with cloud platforms and services (e.g., AWS, Azure) What We Offer: Joining Maersk means becoming part of a global leader that is truly transforming an entire industry. You will have a unique opportunity to make a significant impact on our operations by developing cutting-edge ML solutions. We offer a challenging yet rewarding environment where continuous learning, professional development, and innovative problem-solving are highly valued. You'll work with diverse teams and have the chance to grow your career within a truly international and forward-thinking organization.
