AIML Engineer– Global Data Analytics, Technology (Maersk)
This position will be based in India – Bangalore/PuneA.P. Moller - MaerskA.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 & 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 BriefIn 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 I'll be doing – your accountabilities?Key Responsibilities
- Requirement Gathering & Solution Design: Engage with stakeholders to capture requirements, define use cases, and translate them into technical solutions.
- End-to-End Development: Design, build, test, and deploy robust, scalable, and optimized GenAI/ML systems.
- Software Engineering Practices: Apply best practices in code quality, version control, security, CI/CD pipelines, automated testing, and error handling.
- GenAI Development: Build, fine-tune, and optimize LLMs, multimodal models, and diffusion models for real-world applications.
- RAG & Agentic Systems: Implement Retrieval-Augmented Generation (RAG) pipelines, agentic frameworks, and contextual workflows with MCP.
- NLP & Embeddings: Leverage natural language processing (NLP) techniques and embeddings for semantic search, classification, and personalization.
- ML/DL Engineering:
- Research, design, and implement new machine learning and deep learning models.
- Solve ambiguous business problems with the right data-driven approaches.
- Perform A/B testing and evaluate model/system performance.
- Integration: Develop APIs and services to embed GenAI/ML solutions into enterprise applications and user-facing products.
- Documentation & Collaboration: Produce clear technical documentation of designs, assumptions, and methodologies; collaborate with cross-functional teams while owning execution as an IC.
Required Skills & Experience
- GenAI & NLP Expertise:
- Strong understanding of LLMs, embeddings, transformers, RAG, agentic frameworks, MCP, and multimodal AI.
- Experience with fine-tuning (LoRA, PEFT, instruction tuning) and evaluation (embedding similarity, BLEU/ROUGE, human-in-loop).
- Programming & Data Science:
- Proficiency in Python with solid grounding in data science fundamentals (data cleaning, EDA, preprocessing, feature engineering).
- Experience with ML/GenAI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex).
- Hands-on with vector databases (FAISS, Pinecone, Weaviate, Milvus).
- Software Engineering:
- Experience designing, building, and testing production-grade systems.
- Strong background in software practices (modular design, code reviews, debugging, automated testing).
- Familiarity with pipeline automation and secure development practices.
- MLOps & Deployment:
- Experience with CI/CD, Docker, Kubernetes, and cloud platforms (AWS SageMaker, Azure OpenAI, GCP Vertex AI).
- Monitoring, scaling, and optimizing deployed GenAI/ML models.
Preferred Skills
- Exposure to multimodal systems (text-to-image, speech-to-text, text-to-video).
- Knowledge of data pipelines and scalable vector search architectures.
- Contributions to open source, research, or hackathons in GenAI/ML.
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
- 4+ 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
- Experience with collaborative development workflow: version control (we use github), code reviews, DevOps (incl automated testing), CI/CD
- Strong foundation with expertise in neural networks, optimization techniques and model evaluation Experience with LLMs, Transformer architectures (BERT, GPT, LLaMA, Mistral, Claude, Gemini, etc.). Proficiency in Python, LangChain, Hugging Face transformers, MLOps
- Experience with Reinforcement Learning and multi-agent systems for decision-making in dynamic environments. Knowledge of multimodal AI (integrating text, image, other data modalities into unified models
- Team player, eager to collaborate and good collaborator
Preferred Experiences
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.
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 accommodationrequests@maersk.com.
