What I'll be doing – your accountabilities?
Design, develop, and implement robust, scalable, and optimized machine learning and deep learning models, with the ability to iterate with speed
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
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
AI & Machine Learning
Data Analysis
Machine Learning Pipelines
Model Deployment
Specialized Skills
To be able to understand beyond the fundamentals and can demonstrate in most situations without guidance for the following skills:
Deep Learning
Statistical Analysis
Data Engineering
Big Data Technologies
Natural Language Processing (NPL)
Data Architecture
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 or related discipline with 5+ years of industry experience building cloud-based ML solutions for production at scale, including solution architecture and solution design experience
Good problem solving skills, for both technical and non-technical domains
Good broad understanding of ML and statistics covering standard ML for regression and classification, forecasting and time-series modeling, deep learning
4+ years of hands-on experience building ML solutions in Python, incl knowledge of common python data science libraries (e.g. scikit-learn, PyTorch, etc)
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
Python courseMachine Learning Model DesignDeep LearningData Analysis+16
