Lead Machine Learning Engineer

Summary

Join Tapcheck as a Lead Machine Learning Engineer/Scientist and play a pivotal role in developing and maintaining our Machine Learning & Data Processing capabilities. Collaborate across teams to build new models, improve accuracy, and mentor other engineers. Shape the technical direction of our products, fostering innovation and excellence. This remote-friendly role requires 5+ years of experience in machine learning model development and leadership. You will need expertise in ML tools, Python, SQL, and Agile methodologies. Tapcheck offers competitive base pay, remote work, paid time off, and comprehensive health benefits.

Requirements

• 5+ years in Machine Learning model development, with a focus on Feature Engineering and ML Metrics such as F1 and AUC-ROC
• 3+ years supporting a production SaaS application and previous experience collaborating with SAAS Product teams
• Solid understanding of ML design principles and patterns, and strong expertise in ML Tools such as Tensorflow, BiGML, Vertex AI, and Keras
• Demonstrated understanding of ML Systems Architecture, Databases, and other data architecture components
• 5+ years experience with Python, SQL, R, and SCM tools such as Git
• 5+ years of leadership experience working in a team following Agile SDLC practices
• 3+ years of technical leadership experience working on platforms & system applications in a public cloud context (AWS, GCP, Azure)
• 3+ years delivering Hadoop or Spark systems
• Bachelor’s or Master’s degree in Computer Science or a related experience
• Possess the right to work in the United States without the need for employment-based visa sponsorship now or in the future

Responsibilities

• Identify, evaluate, and normalize data for ingestion and feature scaling
• Design, implement, and test machine learning models
• Employ statistical metrics such as accuracy, precision, F1, and AUC-ROC to evaluate model performance, and conduct cross-validation and hyperparameter tuning to optimize model performance
• Use regularization and ensemble learning to improve model accuracy and reduce overfitting
• Deploying Machine Learning models to public cloud-based production infrastructure, monitoring their performance, and making appropriate changes
• Mentor and coach junior engineers, helping them grow their technical skills
• Conduct code reviews and provide constructive feedback to ensure code quality and adherence to standards
• Collaborate with other teams and stakeholders to ensure seamless integration and compatibility between products and services

Benefits

• Competitive Base
• Remote Work Environment
• Paid Time Off
• Health Insurance
• Dental Insurance
• Vision Insurance
• 401K Match