Backend Engineer

Set up, manage, automate and deploy AI models in development and production infrastructure.

Orchestrate life cycle management of AI Models

Create APIs and help business customers put results of the AI models into operations

Develop MVP ML learning models and prototype applications applying known AI models and verify the problem/solution fit

Validate the AI Models

Make model performant (time and space) based on the business needs

Perform statistical analysis and fine-tuning using test results

Train and retrain systems when necessary

Extend existing ML libraries and frameworks

Processing, cleansing, and verifying the integrity of data used for analysis

Ensuring that algorithms generate accurate user recommendations/insights/outputs

Keep abreast with the latest AI tools relevant to our business domain

Job Qualifications

Bachelor’s or master's degree in Computer Science, Statistics or related field

A Master’s degree in data analytics, or similar will be advantageous.

3 - 5 years of relevant experience in deploying AI models to production

Understanding of data structures, data modeling, and software architecture

Good knowledge of math, probability, statistics, and algorithms

Ability to write robust code in Python/ R

Proficiency in using query languages, such as SQL

Familiarity with machine learning frameworks such as PyTorch, Tensorflow and libraries such as scikit-learn

Worked with well know machine learning models ( SVM, clustering techniques, forecasting models, Random Forest, etc.)

Having knowledge in CI/CD for the building and hosting the solutions

We don’t expect you to be an expert or an AI researcher, but you must be able to take existing models and best practices and adapt them to our environment.

Adherence to compliance procedures in accordance with regulatory standards, requirements, and policies.

Ability to work effectively and independently in a fast-paced agile environment with tight deadlines

A flexible, pragmatic, and collaborative team player with an innate ability to engage with data architects, analysts, and scientists.