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
.
