Hewlett-Packard (HP) | Jobs | ML Ops Engineer | BigDataKB.com | 16-02-22

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Job Location: Chennai

We are currently moving into common infrastructure with ADLS / Azure data warehouse / Analytics zone all being fed by an Enterprise Data Lake (Hadoop / Hive) structure.   The majority of work currently is to improve the robustness of current assets, drive reuse of common metrics and data sets and to empower business reporting.   The future will focus more on analytics, real time data, and near real time data.

  • Build practices in MLOps that combine Machine Learning, DevOps, and Data Engineering, which aim to deploy and maintain ML systems in production reliably and efficiently.
  • Model & Data Versioning Automated Version Control & tracking of model versions, along with the data used to train it, and some meta-information like training hyperparameters.
  • Model Output & Data Validation Automating process of Model output & Data validation with proper metrics relevant to each model used in ML Algorithms
  • Monitoring Build & Production Systems using automated monitoring & alarm tools.
  • Work on onboarding ML and Deep Learning models using ML Engineering Tech stack.
  • Create SOPs for model onboarding, model deployment and support.
  • Provide Model Production Support including trouble shooting, bug fixes and do RCA.
  • Build Model Health monitoring dashboards to track model KPIs, model drift and feedback loop.
  • Uses bug tracking, code review, version control and other tools to organize and deliver work.
  • Collaborate with other teams with different backgrounds / expertise / functions for code review, model migration, deployment, monitoring and alerts

Required Candidate profile

  • 4 to 6 years experience in Design, develop, test, deploy, maintain and improve ML models/infrastructure and software that uses these models
  • Hands-on experience with autoML tools, experiment tracking, model management, version tracking model training (MLflow), model hyperparameter optimization, model evaluation, and visualization (Power BI)
  • Good expertise with Azure stack: Azure Databricks, Azure ML services, ML ops, ADF, Spark
  • Experience working with recommendation engines, forecasting algorithms, data pipelines, or distributed machine learning
  • Sound knowledge and experience with atleast one DL frameworks such as PyTorch, TensorFlow, Keras
  • Experience with container technologies (Docker, Kubernetes etc).
  • Knowledge of data analytics concepts, including bigdata, data warehouse technical architectures, ETL and reporting/analytic tools and environments
  • Contribute to engineering efforts from planning and organization to execution and delivery to solve complex, real world problems
  • Working knowledge on different Algorithms and Machine Learning techniques (supervised, unsupervised, reinforcement, ANN)
  • Working knowledge of SQL based databases.
  • Demonstrated excellent communication, presentation, and problem-solving skills
  • Detail oriented design, code debugging and problem-solving skills
  • Ability to communicate complex technical/architectural problems and propose solutions for the same.

Perks and Benefits 

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