Machine Learning Engineer

About the role

About us:

At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business. We believe in using our advantages to make a positive impact on the world and inspiring others to do the same.

Job Description:

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data generation and data analysis.  You will own all work related to acquiring high-quality data to power the training of our domain-specific models end to end.  You will work closely with other researchers and engineers to empower our next generation of domain-specific models.  We value rapid prototyping, iterating, and shipping new systems quickly.

Required Qualifications:

- BS/MS/PhD in Computer Science or a related field.

- Proficiency in at least one deep learning framework, such as PyTorch.

- Experience in machine learning projects in text or vision, e.g., has trained machine learning models to tackle a specific problem.

- Strong expertise in large stateful distributed systems and data processing.

- Strong proficiency in building large-scale data processing pipelines, familiar with distributed workload (e.g., multiprocessing, Ray, Docker, Kubernetes).

- Proficiency in at least one programming language commonly used in machine learning, such as Python and ability to write clean, maintainable code.

- Excellent problem-solving skills and attention to detail, especially when handling data anomalies and biases to further improve data quality.

Key Competencies

- Active Github contributions are a big plus.

- Experience in building large-scale datasets.

- Familiar with at least one of the following tools for data crawling (e.g. Scrapy), data collection (e.g., VPNs, Selenium), data processing (e.g., Hadoop, Datasketch).

- Building bespoke data processing libraries from scratch.

- Keeping up with state-of-the-art techniques for preparing AI training data.

- Organizing and meticulously bookkeeping data across multiple clouds, of multiple modalities, and from many sources.

- Multilingual which contributes to enriching the language diversity crucial for robust model training.

Responsibilities:

- Design and develop data processing pipelines, including data extraction, data filtering, data labeling, etc.

- Implement machine learning models to improve the quality and diversity of data (especially in the data extraction stage), e.g., quality classifier, document layout model, code verification model, etc.

- Own and lead engineering projects in the area of data acquisition, including web crawling, data ingestion, and processing.