AI/ML Engineer

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