Please fill out this assessment to be considered:
https://www.hackerrank.com/test-v2/cokgoimqe88/bae38f5e200c3b24946a969e67dff6c4
Api code: 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
Google Form:
Company Description
Verita AI is at the forefront of next-generation artificial intelligence, emphasizing the importance of nuance, multimodal reasoning, and human judgment. We are dedicated to building high-trust data pipelines for training and evaluating models across language, vision, audio, and video.
Verita
, meaning “truth,” reflects our commitment to creating contextually enriched, reliable data layers.
Our team spun out of Mercor and comes from Stanford, Harvard, and leading AI organizations. We partner with research labs to build rigorous reinforcement learning environments for evaluating frontier AI systems, creating infrastructure that advances both experimentation and reliability in the field.
Role Description
This is a
remote contract role
for a
Machine Learning Engineer (MLE)
. The MLE will be responsible for designing, implementing, and optimizing machine learning models. This includes data preprocessing, feature engineering, model training, evaluation, and deployment. The role also involves improving multimodal data pipelines, collaborating with cross-functional teams, and staying current with the latest AI research.
As part of the process, candidates will complete a
take-home technical assessment
(turnaround time approximately one week). The assessment is linked above. Those who pass will be invited to interview with a stealth startup led by a CEO who was employee #50 at Anthropic and helped build Claude’s pretraining pipelines.
Compensation:
$40–$200
per hour (contract)
Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field (required)
- Experience with designing and optimizing machine learning models
- Proficiency in data preprocessing and feature engineering
- Ability to evaluate and deploy machine learning models
- Experience with multimodal data pipelines
- Strong programming skills in Python and familiarity with popular ML libraries (e.g., TensorFlow, PyTorch)
- Excellent problem-solving and analytical skills
- Ability to work independently and remotely
- Demonstrated experience in AI research and staying updated with industry advancements