What will you need?

• University Degree in Computer Science, Information Technology, or related field
• 7+ years of experience in the Machine Learning Operations role
• Design the data pipelines and engineering infrastructure to support our BU’s enterprise machine learning systems at scale
• Take offline models data scientists build and turn them into a real machine learning production system
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
• Identify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Support model development, with an emphasis on auditability, versioning, and data security
• Facilitate the development and deployment of proof-of-concept machine learning systems
• Communicate with clients to build requirements and track progress
• Strong analytic skills related to working with structured, semi structured and unstructured datasets
• Docker and Kubernetes
• Experience in using popular MLOps frameworks like Kubeflow, MLFlow, and DataRobot
• Ability to build MLOps pipelines
• Strong Python programming knowledge
• FAST API, Flask, Python code optimization
• Kubeflow, Airflow, ML Flow, Jenkins
• Poetry for package management
• Black, ruff, isort, flake8 for code cleanup
• Github Actions
• Machine learning techniques: Decision Trees, Random Forest, Boosting Algorithm, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl. sentiment analysis, Topic Modeling), Natural Language Generation
• Ability to design and implement cloud solutions - Azure
• Awareness of Agile / Scrum ways of working
• Identify the right modeling approach(es) for given scenario and articulate why the approach fits
• Assess data availability and modeling feasibility
• Review interpretation of models results
• Experience in Logistic industry domain would be added advantage

You should have:

• Certifications in some of the core technologies
• Ability to collaborate across different teams/geographies/stakeholders/levels of seniority
• Customer focus with an eye on continuous improvement.
• Energetic, enthusiastic and results-oriented personality
• Ability to coach other team members, you must be a team player!
• Strong will to overcome the complexities involved in developing and supporting data pipelines