Offer summary

Qualifications:

Master’s degree in Computer Science or related field., 4 years of experience in application development with object-oriented programming languages, including Python/Java., Experience with ETL workflows and data management using AWS GLUE, Spark, and other technologies., Proficiency in developing full model lifecycle solutions using ML frameworks and orchestration tools..

Key responsibilities:

Lead the design and implementation of MLOps solutions for machine learning models.

Improve the stability, security, and scalability of systems.

Develop monitoring tools to ensure the reliability of MLOps infrastructure.

Drive automation initiatives for model deployment and infrastructure provisioning.

Job description

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.