Machine Learning Engineer - 0122 SS #1

Job Title: Machine Learning Engineer

Work Location: Fully Remote
Employment Type: Contract
Bill Rate: $55

Job Summary

We are seeking an experienced Machine Learning Engineer to design, build, deploy, and maintain scalable machine learning solutions. This role focuses on applying ML, AI, statistics, and advanced data analysis to internal operational datasets to solve complex, real-world business problems across multiple teams. The ideal candidate has strong end-to-end ML ownership, robust data engineering skills, and the ability to operate in a production-grade environment.

Key Responsibilities

• Design, develop, deploy, and maintain end-to-end machine learning pipelines and systems

• Apply machine learning, AI, and statistical techniques to solve real-world business problems

• Build scalable data pipelines to support model training, validation, and production inference

• Perform data exploration, feature engineering, model selection, training, and evaluation

• Ensure model performance, reliability, scalability, and maintainability in production

• Collaborate with cross-functional teams to understand requirements and translate them into ML solutions

• Monitor deployed models and pipelines; implement retraining, optimization, and lifecycle management

• Contribute to system architecture, best practices, and technical documentation

Required Skills & Experience

• 5+ years of experience as a Machine Learning Engineer

• Proven experience designing, deploying, and maintaining machine learning pipelines and systems

• Demonstrated ability to build machine learning models end-to-end, from data ingestion to production

• 5+ years of experience with large-scale data pipelines

• Strong Machine Learning and AI domain expertise

• Full-stack engineering experience

• Proficiency in:

  • Python

  • SQL

  • PHP

• Strong background in statistics, data analysis, and applied ML algorithms

Preferred Qualifications

• Experience working at large technology organizations (e.g., Big Tech environments such as Meta, Google, Microsoft, or similar)

• Exposure to enterprise-scale or highly distributed ML systems

Education

• Bachelor’s or Master’s degree in:

  • Computer Science

  • Mathematics

  • Physics

  • Engineering

  • Statistics

  • Or a related quantitative field