Senior Machine Learning Ops Engineer
New
J
JobgetherData Platform
Based in the United StatesFull-TimeSenior
Salary150,500 - 173,000 USD per year
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Job Details
- Experience
- 6+ years
- Required Skills
- AWSDockerPythonSQLKubernetesSnowflakeAirflowFastAPICI/CDTerraform
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, or related field.
- 6+ years of experience in MLOps, platform engineering, DevOps, or data engineering.
- 3+ years of hands-on experience working with AWS cloud infrastructure.
- Strong Python engineering skills, including API and backend development.
- Experience building and operating production machine learning systems.
- Strong knowledge of Docker and modern deployment practices.
- Experience with Kubernetes, ECS, or EKS.
- Experience managing Infrastructure-as-Code using Terraform, OpenTofu, or CloudFormation.
- Strong SQL skills and experience with Snowflake, Databricks, or BigQuery.
- Experience implementing CI/CD workflows and engineering best practices.
- Experience with workflow orchestration tools like Airflow, Dagster, or Prefect.
- Proficiency in testing frameworks such as pytest.
- Strong understanding of Bash and Unix-based environments.
Responsibilities
- Design, deploy, and maintain scalable ML infrastructure supporting model training, batch processing, and real-time inference.
- Build and manage cloud-based infrastructure and services using AWS, Snowflake, and Infrastructure-as-Code.
- Develop and maintain containerized ML deployment solutions using Docker and FastAPI.
- Create and improve CI/CD pipelines, automation frameworks, and testing processes for machine learning systems.
- Partner with Data Science and Engineering teams to productionize models.
- Establish monitoring and observability frameworks for model performance, drift detection, and data quality.
- Improve platform reliability, scalability, security, and governance.
- Contribute to the development of reusable ML infrastructure components and data products.
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