ML Pipeline Engineer - Remote

Overview

An overview paragraph about the job

In Short

• Build and maintain robust, scalable pipelines for data preprocessing, training, and inference.
• Automate machine learning workflows, including feature extraction, model training, and evaluation.
• Deploy machine learning models into production environments, ensuring high availability and performance.
• Monitor production systems for model drift, performance issues, and data quality.
• Collaborate with Data Scientists to integrate models into production environments effectively.
• Optimize infrastructure for cost, performance, and scalability, using cloud platforms and distributed systems.
• Implement CI/CD pipelines for machine learning workflows to enable faster and more reliable deployments.
• Ensure compliance with data governance, security, and regulatory standards in production systems.

Requirements

• Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent experience.
• 3+ years of experience in machine learning engineering, software engineering, and DevOps.
• Strong programming skills in Python and experience with ML libraries.
• Proficiency in cloud platforms and their ML services.
• Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes) is a plus.
• Knowledge of distributed data processing frameworks (e.g., Apache Spark, Hadoop).
• Strong understanding of CI/CD practices and tools for ML pipelines.

Benefits

• Competitive base compensation
• Health and wellness Insurance with generous company contribution (medical, dental, vision)
• Company-paid life insurance, short-term and long-term disability
• 4% 401K match with immediate vesting of Company match
• Continuing Education Opportunities
• Flexible/Open (Uncapped) Paid Time Off (PTO) Policy for Salaried Team Members*
• Competitive Paid Time Off (PTO) Policy for Hourly Team Members*
• Generous Company-paid Holidays