This role will need to overlap 3-5 hours/day with Pacific Standard Time.

How your work will support our growth:

The mission of the SupportLogic Machine Learning (ML) team is to create and leverage cutting-edge ML models, especially Large Language Models (LLMs) that can extract new signals from unstructured data and make insightful, actionable predictions for our customers.

We are responsible for:

• Maximizing the value of SupportLogic to our customers by advancing the frontier of ML performance and Intellectual Property (IP).
• Ensuring ML models deliver consistent, predictable, and improving performance in production environments by working with backend engineering.
• Extracting maximum utility from our predictions for our end users and customers by collaborating with product design, UI, and customer-facing teams.

We seek a Machine Learning Engineer interested in building models our customers can rely on for accurate predictions and reading of signals. You will be working in a fast-moving and growing company; our team is made of self starters who are curious about learning and using new technologies, systems, and processes.

The work you’ll do:

• Validate - Increase confidence of model rollouts by enriching and automating model validation prior to and immediately after deployment.
• Measure - Provide insight into accuracy and relevance of ML model predictions in production by measuring and monitoring model input and output data distributions, as well as user engagement/feedback on predictions.
• Automate - Incorporate user feedback/activity into new ML model training by automation of data collection, model retraining, model measurement, etc., towards a goal of continuous automated model retraining.
• Build - Provide internal tools or incorporate commercial tools (e.g., ClearML) into data scientist workflows for data analysis, feature generation, model development, etc., to boost ML team productivity.
• Collaborate - Bridge the gap between ML research and production-grade backend code by working with other engineering teams to integrate new ML models or APIs into production.

About you (don't worry if you don't have this whole list- we expect you to learn with us):

• Professional experience as a data scientist, machine learning researcher, or machine learning engineer researching and/or building ML products
• Strong proficiency in software development and systems design, ML model management, deployment, and/or versioning.
• Fluent in Python and significant use of common Python data science libraries such as Pandas, numpy, and scikit-learn.
• Experienced with querying and using SQL.
• Experienced building APIs in Python, particularly in FastAPI or Flask.
• A self-starter, with the interest and passion to contribute in a fast-paced startup environment.
• B.S., degree or equivalent in Computer Science, Mathematics, or similar field of study with special focus on machine learning/NLP. M.S or M.Tech is highly desirable.

Preferences:

• Experienced with common Python deep learning libraries such as PyTorch and TensorFlow.
• Experienced with cloud platforms (AWS, GCP, Azure).
• Experienced with MLops platforms such as KubeFlow or MLFlow.
• Understanding and use of Pytest, Docker, and sqlalchemy.

Anticipated Comp Rate: $20-$50k USD/YR Based on experience.