Position: MLOps Engineer
Company: Capital Recruiters
Category: DevOps
Experience required: 3y
English level: upper
Published: 2023-09-01T00:00:00+03:00

Our client is a leading AWS Premier Partner, specializing in cloud migration and complex DevOps projects, mostly for start-ups segment. Their customers are able to plan and execute DevOps best practices of automation self-service, implement and manage Kubernetes, save on budgets, overcome IT complexity and deliver on “time to market”.

The team is looking for a MLOps Engineer to join team and help create leading-edge technology solutions for customers.

ML responsibilities

You will be in charge of the entire machine learning pipeline from the MLOps perspective. You will work with our customers hand-in-hand, and help them build and run machine learning systems at scale.

You will be responsible for:

Work hands-on as an MLOps/DevOps Engineer with Data Scientists and RnD teams
Provision ML AWS resources and infrastructure
Developing MLOps pipelines leveraging the Amazon SageMaker platform and its features
Developing ML-oriented CI/CD pipelines using GitHub Actions, BitBucket or similar tools
Deploying machine learning models in production
Help customer tackle challenges in scale using distributed training frameworks
Learning new skills and technologies quickly

DevOps responsibilities

You will be responsible for:

Using and writing Terraform libraries for infrastructure deployment
Developing CI/CD pipelines for projects of various scales and tech stacks
Maintaining infrastructures and environments of all types from dev to production
Security monitoring and administration

Requirements

Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, Azure or GCP)
Experience with one or more MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc.,
Experience with Docker and Kubernetes
Fluency in Python, a good understanding of Linux, and knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
Ability to understand tools used by data scientists and experience with software development and test automation
Fluent in English, good communication skills and ability to work in a team

Advantages:

A big advantage is working knowledge with Snowflake, BigQuery, and/or Databricks
GCP and/or Azure knowledge (DevOps / MLOps)
ML certification (AWS ML specialty or the like)

Company offer:

Paid vacation and sick leaves;
Medical insurance;
Financial bonuses for AWS certifications achieved;
Referral program – enjoy cooperation with your colleagues and get the bonus;
Compensation for sports and English courses;
In-house online English courses;
An opportunity to work in a community of Cloud infrastructure professionals;
Opportunity to work with cutting-edge DevOps tools and technologies, various of projects & free option to change project if needed;
100% payment for certifications AWS, GCP, K8s, Jenkins, HashiCorp, etc. – pass exams only during working hours.