Assoicate AIML Engineer– Global Data Analytics, Technology (Maersk) This position will be based in India – Bangalore/Pune A.P. Moller - Maersk A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains. Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too. We are responsible for moving 20 % of global trade &amp; 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. The Brief In this role as an Associate AIML Engineer on the Global Data and Analytics (GDA) team, you will support the development of strategic, visibility-driven recommendation systems that serve both internal stakeholders and external customers. This initiative aims to deliver actionable insights that enhance supply chain execution, support strategic decision-making, and enable innovative service offerings. Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyse data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modelling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions. What Ill be doing – your accountabilities?<ul><li>Build and maintain machine learning models for various applications, such as natural language processing, computer vision, and recommendation systems</li><li>Perform exploratory data analysis (EDA) to identify patterns and trends in data</li><li>Clean, preprocess, perform hyperparameter tuning and analyze large datasets to prepare them for AI/ML model training</li><li>Build, test, and optimize machine learning models and experiment with algorithms and frameworks to improve model performance</li><li>Use programming languages, machine learning frameworks and libraries, algorithms, data structures, statistics and databases to optimize and fine-tune machine learning models to ensure scalability and efficiency</li><li>Learn to define user requirements and align solutions with business needs</li><li>Work on AI/ML engineering projects, perform feature engineering and collaborate with teams to understand business problems</li><li>Learn best practices in data / AI/ML engineering and performance optimization</li><li>Contribute to research papers and technical documentation</li><li>Contribute to project documentation and maintain data quality standards</li></ul> Foundational Skills<ul><li>Understands Programming skills beyond the fundamentals and can demonstrate this skill in most situations without guidance.</li><li>Understands the below skills beyond the fundamentals and can demonstrate in most situations without guidance<ul><li>AI &amp; Machine Learning</li><li>Data Analysis</li><li>Machine Learning Pipelines</li><li>Model Deployment</li></ul></li></ul> Specialized Skills <ul><li>To be able to understand beyond the fundamentals and can demonstrate in most situations without guidance for the following skills:<ul><li>Deep Learning</li><li>Statistical Analysis</li><li>Data Engineering</li><li>Big Data Technologies</li><li>Natural Language Processing (NPL)</li><li>Data Architecture</li><li>Data Processing Frameworks</li></ul></li><li>Proficiency in Python programming.</li><li>Proficiency in Python-based statistical analysis and data visualization tool</li><li>While having limited understanding of Technical Documentation but are focused on growing this skill</li></ul> Qualifications &amp; Requirements<ul><li>BSc/MSc/PhD in computer science, data science or related discipline with 1+ years of industry experience building cloud-based ML solutions for production at scale, including solution architecture and solution design experience</li><li>Good problem solving skills, for both technical and non-technical domains</li><li>Good broad understanding of ML and statistics covering standard ML for regression and classification, forecasting and time-series modeling, deep learning</li><li>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)</li><li>Hands-on experience building end-to-end data products based on AI/ML technologies</li><li>Some experience with scenario simulations.</li><li>Experience with collaborative development workflow: version control (we use github), code reviews, DevOps (incl automated testing), CI/CD</li><li>Team player, eager to collaborate and good collaborator</li></ul> Preferred Experiences In addition to basic qualifications, would be great if you have…<ul><li>Hands-on experience with common OR solvers such as Gurobi</li><li>Experience with a common dashboarding technology (we use PowerBI) or web-based frontend such as Dash, Streamlit, etc.</li><li>Experience working in cross-functional product engineering teams following agile development methodologies (scrum/Kanban/…)</li><li>Experience with Spark and distributed computing</li><li>Strong hands-on experience with MLOps solutions, including open-source solutions.</li><li>Experience with cloud-based orchestration technologies, e.g. Airflow, KubeFlow, etc</li><li>Experience with containerization (Kubernetes &amp; Docker)</li></ul> As a performance-oriented company, we strive to always recruit the best person for the job – regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams.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. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing  <a href="mailto:accommodationrequests@maersk.com" target="_blank">accommodationrequests@maersk.com</a>.

Maersk

Associate AI/ML Engineer

Maersk

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