Senior Machine Learning Engineer
Abundant
part-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
Tech Stack
About the role
- Design, debug, and maintain ML systems in realistic, tools-enabled environments
- Work across training, evaluation, and infrastructure to ensure ML systems behave correctly and robustly in practice
Requirements
- 4+ years of professional experience in Machine Learning Engineering, Applied ML, Software Engineering (ML-focused), or related roles
- Strong proficiency in Python, with experience writing production-quality code and working with ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
- Experience training, evaluating, and iterating on ML models, with an emphasis on diagnosing failure modes rather than just optimizing metrics
- Strong understanding of ML evaluation: metrics design, test coverage, error analysis, and tradeoffs between correctness, robustness, and generalization
- Ability to debug complex ML system failures, including issues caused by data, evaluation artifacts, or underspecified requirements
- Comfort working with incomplete specifications and multiple valid solutions, especially in open-ended or real-world tasks
- Experience working with ML pipelines or systems, including training workflows, evaluation harnesses, or model-in-the-loop systems
Benefits
- Flexible hours with a minimum commitment of 20+ hours per week
- Project length 1–2 months, with potential to extend
- Compensation up to $150/task
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine Learning EngineeringPythonproduction-quality codeML librariesPyTorchTensorFlowscikit-learnML evaluationdebugging ML systemsML pipelines
Soft Skills
problem-solvingdiagnosing failure modesworking with incomplete specificationsadaptabilitycommunication