Senior Staff Engineer – Machine Learning Platforms - GOPN

Position Summary:
We are seeking a highly experienced Senior Staff Engineer with 12–15+ years of expertise to lead the design and development of self-serve platforms focused on real-time ML deployment and advanced data engineering workflows. This senior role requires expertise in cloud-native platform engineering, scalable infrastructure development, and end-to-end deployment of machine learning solutions to support business-critical applications.

Responsibilities:

• Lead the design and development of scalable microservices-based platforms using Kubernetes, Docker, and Python (FastAPI) to manage ML workflows and data pipelines.
  
• Architect and manage real-time ML inference platforms with tools like AWS SageMaker and Databricks, ensuring model versioning, monitoring, and lifecycle management.
  
• Build and optimize large-scale ETL/ELT pipelines using PySpark, Pandas, and manage feature stores for consistent, high-quality data.
  
• Design and implement distributed data pipelines integrating tools like DynamoDB, PostgreSQL, MongoDB, and MariaDB.
  
• Oversee the creation of data lakes and data warehouses to support advanced analytics and ML workflows.
  
• Architect and maintain robust CI/CD pipelines with tools such as Jenkins and GitHub Actions for automated testing and deployment.
  
• Drive automation of data validation and monitoring for ensuring data consistency and quality.
  
• Collaborate with cross-functional teams to understand business needs and translate them into technical solutions.
  
• Provide thought leadership, mentor junior engineers, and contribute to technical decision-making across the organization.
  
• Document and maintain comprehensive technical artifacts for architecture and workflows.
  

Required Skills & Qualifications:

• 12–15+ years of experience in platform engineering, data engineering, or DevOps roles with a focus on machine learning.
  
• Advanced proficiency in Python, PySpark, FastAPI, Kubernetes, and Docker.
  
• Deep expertise in AWS services, including SageMaker, Lambda, DynamoDB, EC2, and S3.
  
• Extensive experience designing and optimizing distributed data pipelines with Databricks, PostgreSQL, and other database solutions.
  
• Proven experience building and managing CI/CD pipelines with tools like Jenkins, GitHub Actions, and troubleshooting with tools like New Relic.
  
• Strong leadership skills with a track record of mentoring and guiding engineering teams.
  
• Exceptional communication skills, with the ability to explain complex technical solutions to stakeholders.