Machine Learning Engineer

pay

Required Skills
Python
Machine Learning
MongoDB
About micro1
micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.

Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.

Role Title: Machine Learning Engineer

Role Type: Contractor

Location: Remote

micro1 is engaging Machine Learning Engineers to contribute expertise to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Scope of Work

Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.
Analyze large datasets and leverage MongoDB to manage and retrieve data efficiently for model training and validation.
Collaborate with cross-functional contributors to identify areas for model improvement and implement robust solutions.
Conduct thorough model evaluation, tuning hyperparameters, and benchmarking results to ensure optimal performance.
Document methodologies, experiments, and outcomes to ensure transparent and repeatable workflows.
Integrate data pipelines and preprocessing workflows to streamline training and inference processes.
Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes.

Preferred Qualifications

Demonstrated expertise with Python, including deep familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with MongoDB for data manipulation, storage, and retrieval within machine learning projects.
Strong problem-solving skills and a track record of delivering innovative ML solutions in real-world settings.
Understanding of model evaluation metrics, feature engineering, and effective data preprocessing techniques.
Background in deploying or operationalizing machine learning models in cloud or enterprise environments.
Clear written documentation and communication skills for sharing technical findings and best practices.
Ability to adapt quickly to evolving project requirements and contribute collaboratively in a remote setting.
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