Logo
LegalZoom

Staff Data Scientist (AI/ML/LLM)

LegalZoom, Mountain View, California, us, 94039


Description About LegalZoom We're here to make legal help accessible to all. LegalZoom transformed the legal industry with the launch of our online services and groundbreaking technology in 2001. Since then, millions of customers have counted on us to officially start and run businesses, protect brands and intellectual property, and look after loved ones through wills and trusts. As the industry leader for over 20 years, innovation remains at the center of all we do. We're creative thinkers and problem solvers with a passion for building legal and tax products that make a positive impact on the world, and we're always looking for exceptional people to push us further. With us, you'll do work that's as rewarding as it is challenging with a team where every voice matters and diversity, equality, and inclusion are truly embraced. Together, we'll continue to democratize the law and make a real difference in the lives of millions. Where we work 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. This position will be in our SF Bay Area, LA Metro, or Austin, TX location Overview The Data Science and Engineering team at LegalZoom is transforming the way we leverage large-scale data to enhance decision-making across our products and services. Our team is at the forefront of applying Machine Learning (ML) and Large Language Models (LLMs) to shape operational strategies, improve customer experiences, and optimize our business processes. As a Staff Data Scientist specializing in LLMs and ML, you'll play a pivotal role in developing and deploying state-of-the-art models that drive key business decisions. You will collaborate with cross-functional teams, including Product Managers, Engineers, and Operations leaders, to apply advanced machine learning techniques and language models in areas such as customer interaction, automation, and self-service systems. You'll address complex questions like: How do we improve the customer journey using ML? How can LLMs enhance our contact center operations? Where can we best deploy AI-driven automation? You will 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. You have 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. LegalZoom is a remote-first company and the national range for this role is ($120,000 - $240,000). Actual compensation offered will depend on several factors including but not limited to: geographic location, work experience, education, skill level, and/or other business and organizational needs. In addition, an annual bonus, incentive bonus and/or restricted stock units may be provided as part of the compensation package. You will also receive a full range of medical, financial, and other benefits as seen below. Medical, Dental, Vision Insurance 401k, With Matching Contributions Paid Time Off Health Savings Account (HSA) Flexible Spending Account (FSA) Short-Term/Long-Term Disability Insurance Plus other wellness benefits to include: Fertility Mental Health One Medical Fringe lifestyle benefits up to $250 Join us in making a difference as we build our future and help ensure access to professional legal advice to all LegalZoom is an equal opportunity employer, dedicated to diversity, equality, and inclusion, and provides equal employment opportunities to all employees and applicants for employment. LegalZoom prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Additionally, LegalZoom is enrolled in the E-Verify program. For additional information on E-Verify, please visit Participation and Right to Work pages.