AI/ML Engineer

AIML Engineer– Global Data Analytics, Technology (Maersk)

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.

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