Ds Aiml

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Job Description:

Role is for an AI/ML Engineer role in AI/ML forecasting platform.

Build and maintain data ingestion transformation and feature engineering pipelines to support model training and inference

Build and Maintain systems to power AI/ML model experimentation testing and deployment phases.

Implement & manage Orchestration systems for AI/ML models & Data Pipelines Optimize models & pipelines.

Collaborating with Data Scientists to build the data preprocessing feature engineering & post processing jobs to ensure that the data used for training the models is of high quality & ready.

Collaborating with the Business and Product teams to deliver analytics and reports.

Supports the implementation of security and compliance measures within the AI/ML development process aligning with company policies and industry regulations.

Keeps relevant with the latest technologies and frameworks in AI suggesting improvements and updates to existing systems

Skills :
Experience with Data engineering & building Data/ML pipelines for AI/ML Models &
business analytics & insights.
Experience in applications powered by AI/ML with large dataset
Experience working with ML Operations tools .
Hands-on experience & proficiency in building robust reliable & scalable Data/ML pipelines for Analytics & AI/ML systems working with large sets of structured and unstructured data from disparate sources
MLOps tools and frameworks such as MLflow Kubeflow or Vertex AI
Foundational understanding of ML models
Strong understanding of cloud platforms (AWS Azure or GCP)
Experience managing model registry and implementing versioning best practices.
Model Serving Frameworks
SQL Python Spark PySpark
Big Data systems - Hadoop Ecosystem (HDFS Hive MapReduce) or Cloud
Analytics database like Druid Data visualisation/exploration tools like Superset.
CI/CD GIT
Apache Airflow Cloud Composer
GCP cloud experience Big Query

Experience in retail forecasting or other business prediction models/time series forecasting

Notes:

• product recommendation to help assortment on retail. Mid-level CPG domain experience
• Intermediate knowledge of common DS algorithms (unsupervised approaches like clustering regression methods optimization) - understanding of where these different approaches are applicable and how they might fit together
• Conceptual understanding of the importance of code quality and standards
• Ability to effectively frame and propose a solution to a problem end to end given a use case or simple business problem statement
• Ability to design and execute scientific experiments to answer specific technical questions
• Understanding of basic linear algebra/matrix theory
• Understanding of basic code performance considerations (e.g. understanding big-O)
• Understanding of basic probability & statistics theory

If you like wild growth and working with happy enthusiastic over-achievers youll enjoy your career with us!

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