Senior AIML Engineer

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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