About Us: We are a sustainability focused company focused on reducing the friction in resale by making it easier to sell used clothing online. Our team is comprised of data nerds enthusiastic about making the lives of resellers easier.
Job Description: We are seeking a talented and motivated Data Engineer/Machine learning Engineer to join our dynamic team. The successful candidate will be responsible for managing the data scraping, cleaning the data, and run the labeling pipeline to ensure a seamless handoff to our Machine Learning engineers.
This role is crucial for maintaining the integrity and quality of our data - the foundation of our machine learning models - and ultimately, our business. The ideal candidate will also have experience in building, training, validating, testing, and tuning machine learning models.
Responsibilities:
Data Pipeline Management: Develop and maintain robust data scraping, cleaning, and labeling pipelines with millions + of data points.
Complex Data Pipeline Construction: Plan for the end to end pipeline that uses clean and diverse data collected from our web app for training new machine learning models.
Script Development: Write and optimize scripts for data cleaning using state of the art machine learning models, ensuring that datasets are prepared to the highest standards.
Automation: Create and manage automated prompts for data labeling using multimodal LLMsw, streamlining the data preparation process.
Quality Assurance: Implement processes to ensure the highest quality of data, including validation and verification steps.
Model Training: Engage in hands-on training, validation, testing, and tuning of machine learning models, collaborating closely with ML engineers to improve model performance.
Collaboration: Work with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
Documentation: Maintain comprehensive documentation of data processes, ensuring transparency and reproducibility.
Qualifications:
Preferred Qualifications:
What We Offer:
How to Apply:
Interested candidates should submit their resume, a cover letter detailing their relevant experience, and a portfolio showcasing their most impressive work to laxman@intheloopai.com .
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