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 and accurate results, and working with backend engineers to improve performance in production environments.
• 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 data scientist interested in improving any and all aspects of ML organization efficiency, with the ultimate goal of increasing customer confidence in our ML predictions and our ability to train new ML models or roll out new ML products quickly and efficiently. SupportLogic’s ML products are our core value proposition for our customers, so ML efficiency has a direct connection to our value to our customers and as a company.

You will be working in a fast-moving and growing company; applicants should be self-starting and comfortable learning and using new technologies, systems, and processes. As a data scientist with a strong customer focus, your role is essential for our customers' success. You must have a solid foundation in data science and be enthusiastic about advocating for our data science capabilities.

Your responsibilities will include:

Customer Data Insights: Dive deep into customer data to uncover insights that drive the development and refinement of ML models, ensuring they are closely aligned with customer requirements and behaviors.
Customer Collaboration: Work closely with customer support teams to understand client needs and feedback, translating them into actionable ML improvements.
Model Maintenance: Regularly evaluate and fine-tune ML models to ensure their accuracy and effectiveness in meeting customer expectations.
Innovation and Implementation: Leverage the latest ML technologies, including LLMs and Retrieval-Augmented Generation (RAG) models, to enhance our ML offerings.
Cross-functional Teamwork: Partner with product, UI/UX, and engineering teams to integrate ML innovations seamlessly into our products, ensuring a delightful user experience.
Efficiency and Automation: Streamline model deployment, validation, and retraining processes to accelerate the delivery of ML solutions to our customers.

Who We're Looking For:

Ideal candidates are self-motivated, eager to learn, and passionate about making a tangible impact in a fast-paced startup environment. Your background should include:

Technical Acumen: Solid experience in ML product development, with a particular focus on customer-facing solutions.
Leadership and Collaboration: Ability to lead initiatives and work collaboratively with diverse teams to drive ML innovation from research to production.
Strong Fundamentals: B.S. degree (or equivalent) in Computer Science, Mathematics, or a related field. At least 2+ years of experience in DS/ML engineering, including 1+ years with NLP Models in a production setting.
Tech Proficiency: Expertise in Python, data science libraries (e.g. PyTorch, HuggingFace, Pandas, numpy and scikit-learn), and software development best practices. Familiarity with SQL and the end-to-end lifecycle of ML models.
Master Communicator: We're looking for someone who excels in both technical and non-technical communication, able to articulate complex ideas clearly and effectively through various channels, including reports, presentations, and dashboards, ensuring all stakeholders are aligned and informed.
Desirable Skills: Experience with LLMs, prompt engineering, and quantitatively measuring performance of LLM solutions. Accustomed to modern data warehouses (Snowflake, BigQuery) is a plus.

What We Offer:

Impact: Directly contribute to our mission of revolutionizing customer support through ML.
Growth: Work in a dynamic environment that encourages learning and growth, with opportunities to influence the direction of our ML efforts.
Innovation: Be at the forefront of applying LLMs and other advanced ML models in real-world scenarios, and to support customer needs.
Collaboration: Join a team that values collaboration, innovation, and the delivery of tangible value to our customers.