We are seeking a seasoned AI/ML Engineer with deep expertise in both traditional machine learning and modern Generative AI/LLM technologies. This role will be instrumental in driving our AI transformation, building enterprise-grade solutions that combine classical ML approaches with cutting-edge GenAI capabilities.
Core AI/ML Development
- Partner with business, product, and engineering teams to define problem statements, evaluate feasibility, and design AI/ML-driven solutions that deliver measurable business value
- Lead and execute end-to-end AI/ML projects — from data exploration and model development to validation, deployment, and monitoring in production
- Independently design and implement scalable machine learning solutions and data systems, ensuring end-to-end workflows, large-scale analytics, and reliability
Generative AI & LLM Implementation
- Design and implement RAG (Retrieval Augmented Generation) systems for enterprise knowledge management
- Develop guardrails and safety measures for GenAI applications in production
- Implement cost optimization strategies for LLM inference at scale
- Create synthetic data generation pipelines for model training and testing
- Build and optimize prompt engineering strategies and fine-tuning pipelines
Traditional ML Excellence
- Drive solution architecture using techniques in data engineering, programming, machine learning, NLP, and computer vision
- Implement and refine feature engineering, monitoring, ML pipelines, deploy models in production
- Build real-time inference APIs with sub-second latency requirements
- Develop forecasting models for demand prediction and supply chain optimization
- Create recommendation systems for route optimization and customer solutions
MLOps & Production Engineering
- Champion the scalability, reproducibility, and sustainability of AI solutions by establishing best practices in model development, CI/CD, and performance tracking
- Ensure readiness for production releases, focusing on testing, monitoring, observability, and maintaining scalability
- Implement comprehensive model versioning, registry, and rollback strategies
- Build automated retraining pipelines and drift detection systems
Leadership & Collaboration
- Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews
- Translate technical outputs into actionable insights for business stakeholders through storytelling and data visualizations
- Drive cross-team and cross-discipline initiatives to optimize workflows and enhance collaboration
- Identify and evangelize the adoption of emerging tools, technologies, and methodologies across teams
Technical Requirements
Essential Skills
Programming & Data Engineering:
- Advanced proficiency in Python, SQL, PySpark
- Experience with Docker, Kubernetes for containerization
- Strong software engineering practices (clean code, testing, documentation)
Cloud & Infrastructure (Azure preferred):
- Databricks, Azure ML, ADF, Web Apps
- Experience with distributed computing and big data processing
- Infrastructure as Code (Terraform, ARM templates)
LLM/Generative AI Stack:
- Hands-on experience with foundation models: GPT-4, Claude, Gemini
- LLM frameworks: LangChain, LlamaIndex, LangGraph
- Vector databases: Pinecone, Chroma, pgvector
- Fine-tuning techniques: LoRA, QLoRA, PEFT
- Hugging Face ecosystem (Transformers, Datasets, Hub)
- Embedding models and semantic search implementation
Traditional ML/Deep Learning:
- Deep learning frameworks: TensorFlow, PyTorch, JAX
- Classical ML: scikit-learn, XGBoost, LightGBM, Regression and Classification
- Strong expertise in NLP, Time Series Forecasting
- Experience with recommendation systems and reinforcement learning
- Solid understanding of model evaluation, optimization, bias mitigation, and monitoring.
MLOps & Monitoring:
- MLflow, Weights & Biases for experiment tracking
- GitHub Actions, Azure DevOps for CI/CD
- Model monitoring and A/B testing frameworks
Qualifications
Required
- 10+ years of hands-on experience delivering enterprise-grade AI/ML solutions
- Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or related quantitative field
- Proven track record of deploying ML models in production at scale
- Strong business acumen and ability to bridge the gap between data and decisions
- Experience leading cross-functional AI initiatives
Preferred
- PhD in relevant field
- Prior understanding of shipping and logistics domain
- Open source contributions to ML projects
- Experience with agentic workflows and autonomous systems
What We Offer
- Opportunity to work on cutting-edge AI projects at global scale
- Access to state-of-the-art computing resources and tools
- Collaborative environment with top AI/ML talent
- Professional development and conference attendance support
- Competitive compensation and benefits package
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.
