Job Description
Chegg is on a mission to make education more effective for every student, and AI is central to that vision. To train our models well, we need people who already think like machine-learning engineers. As an AI & Machine Learning Consultant, you will design evaluation tasks, assess model outputs, and produce the high-quality training annotations that move our AI forward. This is a flexible, remote freelance engagement — no fixed hours, no commute.
Core Responsibilities
- Create rigorous evaluation prompts and training tasks spanning supervised learning, neural network architectures, natural language processing, and computer vision
- Examine AI-generated model outputs and statistical analyses for accuracy, soundness of reasoning, and alignment with established ML best practices
- Develop scoring rubrics and quality criteria that objectively measure AI performance on quantitative machine-learning benchmarks
- Produce annotated gold-standard solutions across data science and ML topics that serve as the reference benchmark for AI assessment
- Log systematic error patterns in AI outputs and communicate findings clearly so the research team can act on them efficiently
Key Qualifications
- Master’s or PhD in Computer Science, Data Science, Electrical Engineering, or a quantitative field; hands-on ML or deep-learning experience in industry or academic research is a plus but not required
- Solid command of Python and familiarity with at least one major framework such as TensorFlow, PyTorch, or scikit-learn
- Comfortable working with NumPy, pandas, and standard data-wrangling pipelines
- Able to write technical English with precision — your annotations need to be unambiguous enough for a model to learn from
- Reliable and organised when working independently on asynchronous task batches
Nice to Have
- Hands-on experience with RLHF workflows, LLM benchmarking, or preference data curation
- Research background in NLP, reinforcement learning, or computer vision
- Published work or open-source contributions in machine learning
- Prior involvement with A/B testing, causal inference, or experimental design
Why Chegg
- Fully remote — work from anywhere on a schedule you control
- Flexible task-based format, typically 10–40 hours per week
- Your expertise directly shapes AI tools used by millions of students worldwide
- Ongoing project opportunities for contributors who deliver quality work