Alignerr
Software Engineer - Machine Learning (Contract)
Alignerr, San Francisco, California, United States, 94199
Software Engineer - Machine Learning (Contract)
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This range is provided by Alignerr. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $90.00/hr - $120.00/hr
SWE - Machine Learning (Contract)
Labelbox
Remote (UnitedStates preferred) Shape the data that powers frontier AI
Quick facts
Engagement - Hourly, at‑will contractor
Schedule - Fully remote & asynchronous (min.15hrs/week)
Pay Range (US) - $25–$100 per hour
Start Date - Rolling — staffed as projects launch
What You’ll Do
Review and evaluate AI-generated machine learning code (e.g., Python, TensorFlow, PyTorch, scikit-learn) for correctness, efficiency, scalability, and clarity
Write high-quality machine learning solutions to modeling, data processing, and deployment problems across varying difficulty levels
Create clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving strategies
Identify and flag edge cases or ambiguities in problem statements, datasets, or AI-generated responses
You’re a great fit if
Fluent in English, with strong written communication skills and the ability to clearly explain machine learning concepts and code
Expertise in machine learning: Deep familiarity with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), model development, data preprocessing, and deployment best practices
3–5 years of experience with machine learning projects, pipelines, or tools (e.g., model training, evaluation, MLOps, cloud deployment) is a plus
Bachelor’s degree (or pursuing one) in Computer Science or a related field. Master’s or PhD preferred, but not required.
Bonus: Experience with data labeling, RLHF, or other AI training projects
About The Role
Flexible workload — work from anywhere, on your own schedule
High impact — your craft directly improves models used by top AI labs & Fortune500 teams
Clear ownership — know exactly what success looks like and have autonomy to deliver
Growth potential — consistent high performers spearhead new programs and mentor incoming SMEs
Interview process
Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.
Domain-specific Zara interview to assess your ML expertise, including ML algorithms, models, and training strategies.
About Labelbox Labelbox builds the data engine that accelerates breakthrough AI. Our platform, expert services, and marketplace let teams iterate on data as nimbly as they iterate on code, enabling safer, smarter models in production. We’re backed by SoftBank, AndreessenHorowitz, BCapital, GradientVentures, DatabricksVentures, and KleinerPerkins, and trusted by leading research labs and enterprises worldwide.
Ready to Apply? Click
“Apply”
above, and take one or more domain specific assessments. We review candidates on a rolling basis and will contact you if your background matches an active project.
#J-18808-Ljbffr
This range is provided by Alignerr. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $90.00/hr - $120.00/hr
SWE - Machine Learning (Contract)
Labelbox
Remote (UnitedStates preferred) Shape the data that powers frontier AI
Quick facts
Engagement - Hourly, at‑will contractor
Schedule - Fully remote & asynchronous (min.15hrs/week)
Pay Range (US) - $25–$100 per hour
Start Date - Rolling — staffed as projects launch
What You’ll Do
Review and evaluate AI-generated machine learning code (e.g., Python, TensorFlow, PyTorch, scikit-learn) for correctness, efficiency, scalability, and clarity
Write high-quality machine learning solutions to modeling, data processing, and deployment problems across varying difficulty levels
Create clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving strategies
Identify and flag edge cases or ambiguities in problem statements, datasets, or AI-generated responses
You’re a great fit if
Fluent in English, with strong written communication skills and the ability to clearly explain machine learning concepts and code
Expertise in machine learning: Deep familiarity with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), model development, data preprocessing, and deployment best practices
3–5 years of experience with machine learning projects, pipelines, or tools (e.g., model training, evaluation, MLOps, cloud deployment) is a plus
Bachelor’s degree (or pursuing one) in Computer Science or a related field. Master’s or PhD preferred, but not required.
Bonus: Experience with data labeling, RLHF, or other AI training projects
About The Role
Flexible workload — work from anywhere, on your own schedule
High impact — your craft directly improves models used by top AI labs & Fortune500 teams
Clear ownership — know exactly what success looks like and have autonomy to deliver
Growth potential — consistent high performers spearhead new programs and mentor incoming SMEs
Interview process
Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.
Domain-specific Zara interview to assess your ML expertise, including ML algorithms, models, and training strategies.
About Labelbox Labelbox builds the data engine that accelerates breakthrough AI. Our platform, expert services, and marketplace let teams iterate on data as nimbly as they iterate on code, enabling safer, smarter models in production. We’re backed by SoftBank, AndreessenHorowitz, BCapital, GradientVentures, DatabricksVentures, and KleinerPerkins, and trusted by leading research labs and enterprises worldwide.
Ready to Apply? Click
“Apply”
above, and take one or more domain specific assessments. We review candidates on a rolling basis and will contact you if your background matches an active project.
#J-18808-Ljbffr