Full Time
Software Engineer - Machine Learning
Alignerr
Contract
Technology, Information and Internet
United States
???* / year
Job Description
SWE - Machine Learning (Contract)
Labelbox
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 & Fortune 500 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, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins, 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.
Labelbox
- Remote (United States preferred) Shape the data that powers frontier AI
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 & Fortune 500 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, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins, 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.
??? people applied to this job
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