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About Senzcraft:Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process for the Future. Using intelligent process automation technologies.We have a suite of SaaS products and services, partnering with automation product companies.Please visit our website - more detailsOur AI Operations SaaS platform – on linkedin -> is awarded by Analytics India Magazine in it’s report “State of AI in India” as a “Niche AI startup”. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.Job Description:Role: Data EngineerExperience:3-5 YearsLocation: Bangalore (Hybrid)About the RoleThis is for an AI/ML Engineer role in AI/ML Lowes forecasting platform.Build and maintain data ingestion, transformation, and feature engineering pipelines to support model training and inferenceBuild 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 Job DescriptionSkills :· 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 QueryExperience in retail forecasting or other business prediction models/time series forecasting