Machine Learning Engineer Apprentice

Summary

Join Fetch's ML Engineering team as a Machine Learning Apprentice and contribute to building intelligent systems for users and partners. This 12-16 week apprenticeship involves the full machine learning lifecycle, from data management to large-scale deployment. You'll work on challenging problems, collaborating with various engineering teams. The role requires strong programming skills (Python preferred), experience with ML model building (PyTorch or TensorFlow), cloud deployment (AWS), and testing methodologies. Fetch offers a competitive hourly rate of $50 and a flexible work arrangement (office or remote in the US). The program is not for currently enrolled full-time students.

Requirements

• Possess a solid foundation of fundamental or object-oriented programming skills; proficiency in Python is preferred but other languages are acceptable
• Have experience building and/or training ML models using a Python Framework, such as PyTorch or TensorFlow, in a classroom setting or hands-on environment (e.g., prior work experience, side projects, research, or coding competitions)
• Have experience deploying applications to a public cloud environment (e.g., AWS)
• Have experience with test writing and quality assurance methodologies
• Demonstrate a passion for tackling challenging and ambiguous problems in a fast-paced environment
• Possess the ability to effectively communicate across a variety of technical and nontechnical audiences
• Have a desire to grow your software engineering skills through collaboration, open communication, direct feedback, and knowledge sharing
• Ability to work full-time (40 hours per week) from either one of Fetch’s offices or remotely, in the United States, for a fixed term of 12-16 weeks
• Not be actively enrolled in a full-time, degree-seeking program

Responsibilities

• Contribute to the vision of enabling intelligent systems for end users, internal stakeholders, and external partners
• Work on solving challenging problems at the intersection of developing the models and the infrastructure needed to operationalize them at scale
• Participate in the full life-cycle of machine learning, including data labeling/collection/management, model development, and deploying to large-scale production settings
• Collaborate closely with backend, devops and data engineers on focused teams

Preferred Qualifications

• Have statistical testing and analysis experience (e.g., A/B testing, experimental design); understanding the math behind what makes these models work
• Have experience working with compilers such as ONNX, TensorRT, Triton, or CUDA
• Have experience with search, ranking, or ads
• Have experience building fraud detection models
• Have experience with model servers like TFServing/TorchServe/Triton
• Have experience collaborating cross-functionally with backend and mobile engineers, devops engineers, data scientists, et al

Benefits

• Hourly pay of $50/hour
• Ability to work remotely or from Fetch’s offices