Sr Machine Learning Operations Engineer

AI overview

Lead the design and development of on-premise and cloud MLOps solutions while enhancing system performance and automation initiatives.

Job Responsibilities

  • Lead the design, development and implementation of on-premise and cloud MLOps solutions that support the delivery of machine learning model.
  • Improve stability, security, efficiency and scalability of systems.
  • Build scalable and efficient data pipelines and model training and deployment systems.
  • Develop and maintain monitoring and management tools to ensure the reliability and performance of on-premises MLOps infrastructure.
  • Drive automation initiatives for model deployment and infrastructure provisioning.

Qualifications

  • Master’s degree in Computer Science or related field.
  • 4 years of related experience.
  • Required skills:
    • Application development with object-oriented programming languages, including Python/Java (4 yrs).
    • Experience building ETL workflows, data warehouse solutions, and data management using AWS GLUE, Spark, Kafka, RDBMS, HDFS, and BigQuery (4 yrs).
    • Experience in developing and maintaining full model lifecycle solutions, including model training, evaluation, inference, deployment, and monitoring using ML frameworks including PyTorch/TensorFlow, workflow orchestration tools including Kubeflow/Airflow, cloud workflow platforms including Databricks/SageMaker, and APM monitoring tools including Grafana and Datadog (4 yrs).
    • Build infrastructure and SDK tooling to provide data scientists and ML Engineers with access to specialized data augmentation, curation, and visualization tools for CVML model development (3 yrs).
    • Create CI/CD build and release pipelines with GitLab/GitHub/Jenkins for code and model deployment, and using Terraform/CloudFormation for infrastructure deployment (2 yrs).
    • Analyze and build job orchestration services to scale machine learning tasks on both on-premises and cloud infrastructure in a cost-effective way, including Kubernetes, Airflow, GCP Composer, and Kubeflow (3 yrs).
    • Experience with container orchestration with Kubernetes, microservices architecture, and cloud platforms including AWS and GCP (3 yrs). 
  • This is a 100% remote position.

Full time. $226,158 - $275,000/year. Please visit https://bluerivertechnology.com/join-us/ to apply. 

#LI-DNI

We’re Blue River, a team of innovators driven to create intelligent machinery that solves monumental problems for our customers. We empower our customers – farmers, construction crews, and foresters - to implement safer and more sustainable solutions, driving increased profitability with less reliance on scarce labor. We believe that focusing on the small stuff – pixel-by-pixel and task-by-task - leads to big gains.   Blue River Technology aligns with John Deere’s vision to “innovate on behalf of humanity” by quickly identifying and solving high-value, high-uncertainty challenges in AI, machine learning, computer vision, and robotics.

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Salary
$226,158 – $275,000 per year
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