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, you'll enjoy your career with us!

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