Remote Machine Learning Engineer, Computer Vision

Hire Feed; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Hire Feed is seeking a Python Machine Learning Engineer to design, develop, and deliver advanced ML solutions in a remote, full-time role.

The position combines hands-on coding with technical leadership, mentoring team members, and aligning ML initiatives with business goals across product and engineering functions.

Applicants should have 4 years of hands-on ML experience, strong Python expertise, and a track record applying time-series forecasting and natural language processing.

Qualifications

• Bachelor’s or master’s degree in CS, ML, AI, statistics, or related quantitative field.
• 4 years of hands-on data science and ML development experience.
• Proficiency in supervised/unsupervised learning, time-series forecasting, and NLP.
• Experience with Python and core data science libraries.
• Strong data preprocessing, feature engineering, and model tuning skills.

Responsibilities

• Own end-to-end ML solution development from data pipelines to deployment and monitoring.
• Translate business objectives into robust ML architectures that capture context.
• Collaborate with product, engineering, and business stakeholders to define problems and success metrics.
• Evaluate and optimize models for performance, scalability, and accuracy using state-of-the-art techniques.
• Stay current with AI/ML research and apply relevant innovations.

Skills

Python

Pandas

NumPy

Scikit-learn

Time-series forecasting

NLP

PyTorch

Keras

Education

Bachelor's or Master’s in CS/ML/AI/Statistics

Tools

PyTorch

Keras

Scikit-learn

Job description

Hire Feed is seeking a Python Machine Learning Engineer to design, develop, and deliver advanced ML solutions in a remote, full-time role.

The position combines hands-on coding with technical leadership, mentoring team members, and aligning ML initiatives with business goals across product and engineering functions.

Applicants should have 4 years of hands-on ML experience, strong Python expertise, and a track record applying time-series forecasting and natural language processing.