Python Machine Learning Engineer (Freelance)

About the role

Medib Pme is hiring a part-time Python Machine Learning Engineer as a contractor assignment. You will own end-to-end data science and machine learning solutions, from data pipelines and model design to deployment and monitoring. The work is fully remote, with a 3-month term starting next week, and the expected start date is next week.

Key responsibilities

• Own end-to-end DS/ML solution development, from data pipelines and model design to deployment and monitoring.
• Translate business objectives into robust ML architectures that capture business logic and context.
• Collaborate with Product, Engineering and Business stakeholders to define problem statements and success metrics.
• Evaluate and optimize models for performance, scalability and accuracy.
• Stay current with AI/ML research and apply relevant innovations.

Required profile

• Bachelor's degree in computer science, machine learning, AI, statistics or a related quantitative field.
• 4+ years of hands-on DS/ML development experience.
• Proven ability to design scalable, production-grade ML systems.
• Time commitment of at least 4 hours per day and a minimum of 20 hours per week, with a 4-hour overlap with PST; three options available (20, 30 or 40 hours per week).
• Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey or Mexico.

Required skills

• Supervised and unsupervised learning, time-series forecasting, NLP and computer vision.
• Statistical modelling and inference.
• Python and core libraries such as Pandas, NumPy and Scikit-learn.
• Data preprocessing, feature engineering, model tuning and evaluation metrics.
• Preferred: deep learning (CNNs, RNNs, transformers), cloud platforms (Databricks, AWS) and PySpark.

What we offer

• Pay of $8,000-$10,000 per month.
• Fully remote work on cutting-edge AI projects with leading LLM companies.
• No paid leave, as this is a contractor assignment.

The process involves two interview rounds: a 60-minute technical interview and a 15-minute onboarding and cultural discussion, about 75 minutes total.