MLOps engineer

• Posted 60+ days ago • Updated 10 hours ago
Full Time
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Quantitative Research
  • Continuous Integration
  • Continuous Delivery
  • Machine Learning (ML)
  • Data Management
  • Testing
  • Python
  • scikit-learn
  • TensorFlow
  • PyTorch
  • SQL
  • Extract
  • Transform
  • Load
  • Pandas
  • Docker
  • Kubernetes
  • Cloud Computing
  • Amazon Web Services
  • Machine Learning Operations (ML Ops)
  • Finance
  • Databricks
  • English

Summary

Project description

Work alongside software engineers and data scientists to ensure that quantitative research models are effectively developed, tested, and deployed in production environments.

Responsibilities

Creation and maintenance of CI/CD pipelines for efficient deployment of ML models

Data management

e.g. connect with data sources and create ETL pipelines, cleanse the data, create datasets for model retraining

Create pipelines for automated model testing

Skills

Must have

1.Strong knowledge of Python and familiarity with relevant libraries, e.g. scikit-learn, TensorFlow, and PyTorch.

2.Data

SQL, ETL, Pandas.

3.Containerization (Docker / Kubernetes) and Cloud (AWS).

Nice to have

Experience in applying MLOps principles to financial domain.

Familiarity with Databricks.

Other

Languages

English: C1 Advanced

Seniority

Senior
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10335530
  • Position Id: 4c31e1f8974759604cf7bda3792fc345
  • Posted 30+ days ago
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