[Hiring] MLOps Developer @Software Technology

Role Description

Role: MLOps Developer

Position: Remote

Duration: Long Term

Notes: Candidate must be willing to be part of on-call rotation.

Your future duties and responsibilities:

• Monitoring - Actively monitor ML jobs through logging, metrics, and alerts.
• Incident Management – Address job failures. Rerun jobs, maintain model/job versions in production.
• Infrastructure Scalability - Scale infrastructure to handle production workloads. Tuning, capacity planning, cost optimization.
• Compliance and Security - Apply security best practices. Encrypt data, manage secrets, enforce access controls.
• Technical Support - Troubleshoot integration and infrastructure issues.
• Operations Review – Monthly Incident management summary, Change management summary and other support metrics.
• Model Re-training - Schedule regular retraining of models on new data. Manage code and config changes needed for retraining.
• Model Evaluation - Continuously evaluate model performance on test data. Watch for statistical validation issues.
• Data Validation - Monitor production data inputs. Check for statistical changes, missing values, outliers, errors.
• Dependency Management - Manage libraries, frameworks, ML pipelines. Keep versions aligned across dev, test, prod environments.
• Update Python package versions for Airflow and Lambda if libraries become deprecated and other components and services as needed to customize the environment.
• DevOps – Use version control, Infrastructure as Code, and Configuration Management tools to develop automation which deploys code base.
• Automation – Programmatically define repeatable and reliable tasks which reduce operational overhead.
• Testing – Programmatically enforcing quality standards related to the application, automation, and underlying ML models.

Qualifications

• 3-7 years of proven experience in the following areas:

Requirements

• Cloud:
• AWS CLI
• AWS SDK (boto3)
• Parameter store & Secrets Manager
• Lambda
• Data Engineering:
• SQL (Ability to write, Debug, and optimize queries)
• DynamoDB
• Redshift
• Programming: IDE (VS Code / PyCharm)
• Testing (unit test/pytest/mock)
• Python
• Machine Learning:
• ML Development (Sage Maker)
• ML Programming (Pandas, NumPy, Scikit Learn, Matplotlib, lightgbm)
• Modeling
• DevOps:
• General Linux Terminal (ps, awk, grep, netstat, etc.)
• Shell Scripting (BASH)
• YAML, IaC (Terraform, Cloud Formation)
• CI/CD (Code Build, Code Deploy)
• Orchestration (Apache Airflow)
• Containerization (Docker, Kubernetes)

Company Description