Job Description

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.



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