Must have at least a bachelor's degree in Computer Science or similar.
Min. 2 years of relevant work experience.
Proficient in Basic Machine Learning concepts: algorithms, evaluation procedures, etc, and dealing with Common failure modes. Experienced in at least one area of application (E.g. CV, NLP, etc)
Has a sound knowledge of mathematical concepts like Linear Algebra, Probability and Statistics, Calculus
Proficient in framework & libraries such as Numpy, Pandas, Matplotlib, Scikit-learn and a good grasp of at least one of Tensorflow or Pytorch. Familiar with Flask, FastAPI or Django, and some domain-specific tools (e.g: opencv, spacy, etc)
Good Grasp on programming language and concepts such as Python + OOP + SOLID, Data Structures and Algorithms, RESTful APIs, and familiar with Architecture Design
Good Grasp of software tools and platforms such as git, conda, pip, jupyter, Docker, and at least one cloud platform like AWS/GCP
Good grasp of a database such as SQL/NoSQL
Has a good grasp of agile processes like Sprint and Kanban
Good Team Management, Communication, and Problem-Solving Skills
Develop AI applications to adhere to designs that support business requirements for internal and external clients.
Research and develop machine learning models and work on the whole ML pipeline: data collection, wrangling, pre-processing, model building, evaluation, and deployment
Perform data analysis to uncover insights that can be immediately actionable or can inform decisions around the ML process.
Take initiative and ownership in writing requirement specifications and design documents for a variety of development tasks including feature development, database design, and system integrations.
Preparation, drafting, and review of software documentation and project reports to meet internal and client requirements.
Orchestrate deployment, monitoring, and maintenance of ML applications as per requirement.
Lead one or more projects in different capacities (if required)
Guide other developers and help them (as required) to do their work and look for ways to improve overall team output.
Take on Leadership roles (e.g: Supervisorial) as required.