Description
In an effort to foster a better work-life balance, LegalZoom is committed to a remote-first work environment. Our Austin, Beaverton, Frisco, LA Metro, and SF Bay Area offices allow our Zoomers to collaborate with teammates and offer special onsite events, lunches, and more.
- Lead the application of ML and LLM technologies to improve LegalZoom’s product offerings, from automating customer interactions to optimizing internal operations.
- Drive operational and product strategies by considering long-term impacts of AI and ML solutions, not just immediate analysis.
- Build, fine-tune, and deploy LLMs for various customer-facing applications such as chatbots, automated response systems, and content generation.
- Design and conduct machine learning experiments, utilizing A/B testing, reinforcement learning, and causal inference, to validate hypotheses and optimize models.
- Interpret results of ML models and experiments to make strategic and tactical recommendations to enhance customer engagement and internal efficiencies.
- Develop scalable data pipelines and models to support the implementation of LLMs and other ML systems, ensuring robust, reliable performance.
- Collaborate closely with Product, Engineering, Sales, and Operations teams to integrate ML/LLM solutions into their workflows and ensure they have the data-driven insights they need.
- Continuously improve the team's machine learning codebase and best practices, with a focus on scalability, performance, and data hygiene.
- M.S. or Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or related quantitative field. (If M.S. degree, a minimum of 2+ years of industry experience required; if Bachelor's degree, a minimum of 3+ years of industry experience with ML models and systems).
- Expertise in Machine Learning algorithms and LLM architectures (e.g., transformer models, GPT-based models).
- Experience in developing, fine-tuning, and deploying LLMs and other advanced ML models in production environments.
- Proficiency in Python
- Experience with cloud-based platforms and ML infrastructure (e.g., AWS, GCP, Azure) to scale model development and deployment.
- Advanced SQL expertise for data manipulation and analysis.
- Strong communication skills to explain complex ML and LLM concepts to non-technical stakeholders and influence decision-making at the leadership level.
- Remote Employees should confirm that the internet service available has adequate bandwidth to support all work processes.
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