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Job Description

Description :


- 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.


- Design, develop, and implement robust, scalable, and optimized machine learning and deep learning models, with the ability to iterate with speed


- Write and integrate automated tests alongside models or code to ensure reproducibility, scalability, and alignment with established quality standards


- Implement best practices in security, pipeline automation, and error handling using programming and data manipulation tools


- Identify and implement the right data-driven approaches to solve ambiguous and open-ended business problems, leveraging data engineering capabilities


- Research and implement new models, technologies, and methodologies and integrate these into production systems, ensuring scalability and reliability


- Apply creative problem-solving techniques to design innovative tools, develop algorithms and optimized workflows


- Independently manage and optimize data solutions, perform A/B testing, evaluate performance and evaluate performance of systems


- Understand technical tools and frameworks used by the team, including programming languages, libraries, and platforms and actively support debugging or refining code in projects


- Contribute to the design and documentation of AI/ML solutions, clearly detailing methodologies, assumptions, and findings for future reference and cross-team collaboration


- Collaborate across teams to develop and implement high-quality, scalable AI/ML solutions that align with business goals, address user needs, and improve performance


- Guide junior and associate AI/ML engineers through technical mentoring, code reviews, and solution reviews.


Foundational Skills :


- Have mastered the concepts and can demonstrate Programming skills in complex scenarios.


- Understands the below skills beyond the fundamentals and can demonstrate in most situations without guidance


1. AI & Machine Learning


2. Data Analysis / Engineering


3. Machine Learning Pipelines


4. Model Deployment and Tuning


5. Solution Architecture


Specialized Skills :


- To be able to understand beyond the fundamentals and can demonstrate in most situations without guidance for the following skills :


1. Simulation and Optimization Techniques


2. Advanced Statistical Analysis


3. Deep Learning


4. Big Data Technologies


5. Data Processing Frameworks


- Understands the basic fundamentals of Technical Documentation and can demonstrate in common scenarios with some guidance


Qualifications & Requirements :


- BSc/MSc/PhD in computer science, data science, mathematics, statistics or related discipline with 8+ years of relevant industry experience building cloud-based AI/ML solutions for production at scale, including solution architecture and solution design experience


- A problem solver with scientific rigor, strong business acumen, and the ability to bridge the gap between data and decisions.


- Good broad understanding of ML and statistics covering standard ML for regression and classification, forecasting and time-series modelling, deep learning


- 6+ years of hands-on experience building ML solutions in Python, incl knowledge of common python data science libraries (e.g. scikit-learn, PyTorch, etc)


- 3+ years of experience with simulation methods (Monte Carlo, Discrete Event or Agent Based) and respective Python libraries (e.g. SimPy)


- Strong foundational experience with Reinforcement Learning and multi-agent systems for decision-making in dynamic environments.


- 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


- Expertise in neural networks, optimization techniques and model evaluation is a plus, as well as experience with LLMs, Transformer architectures (BERT, GPT, LLaMA, Mistral, Claude, Gemini, etc.). Proficiency in Python, LangChain, Hugging Face transformers, MLOps


- 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)


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Launched in 2011, our Strategies for Success Programme has helped more than 2,300 women across our global operations to maximise their career potential. Cassia Sanchez is a Product Manager at Maersk, as well as a Strategies for Success alumni. Watch the video to learn more about her experiences on the programme....

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