Principal Machine Learning Engineer
Thrive Market
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ABOUT THRIVE MARKET Thrive Market was founded in 2014 with a mission to make healthy and sustainable living easy and affordable for everyone. As an online, membership-based market, we deliver the highest quality healthy, and sustainable products at member-only prices, while matching every paid membership with a free one for someone in need. Every day, we leverage innovative technology and member-first thinking to help our over 1,700,000+ members find better products, support better brands, and build a better world in the process. We are also a Certified B Corporation, a Public Benefit Corporation, and a Climate Neutral Certified company. Join us as we bring healthy and sustainable living to millions of Americans in the years to come. THE ROLE As Principal Machine Learning Engineer, you'll bridge hands-on MLOps execution with research-level thinking, a combination that spans everything from infrastructure to publication-grade experimentation. You'll read and implement cutting-edge ML papers, debate architecture and statistical methodology with the engineering team, and translate model results into clear business impact at company All Hands. Given how much large language models have reshaped what's possible, you'll also help shape Thrive Market's long-term vision for search and discovery. It's a role that runs the full arc from research to production to business outcomes, with real latitude to define how that work gets done. RESPONSIBILITIES: Build new ML systems from the ground up, close data gaps as they arise, and maintain and improve the existing ML pipeline. Read and implement ML papers on alternative model architectures, then run training experiments to benchmark results against current production models. From your scope help define the long-term search vision, especially given how LLMs have shifted what's possible Stand up and manage infrastructure, such as a Redis cluster, to support ML workloads. Weigh in on and help drive architecture decisions and statistical methodology alongside the broader engineering team. Help shape Thrive Market's long-term vision for search and discovery, informed by how large language models have changed what's possible to build. From your scope help define the long-term search vision, especially given how LLMs have shifted what's possible Present model results and roadmap, including business and revenue impact QUALIFICATIONS: 8+ years of machine learning engineering spanning both MLOps and research-oriented work, with demonstrated principal-level impact across the full loop from research paper to production implementation to business impact presentation Hands-on experience reading and implementing ML papers, and running comparative training experiments to evaluate new model architectures against production baselines Experience building and operating ML infrastructure and pipelines, such as standing up a Redis cluster Experience with, or an informed perspective on, search and discovery systems, particularly how large language models have changed what's feasible to build in house versus buy Comfortable operating as a cross-functional driver, not just an individual contributor, able to debate architecture and statistical methodology across teams Experience presenting technical results and roadmaps, including business and revenue impact, to broad or executive audiences PREFERRED: Hands-on experience with search, personalization, recommendations, ranking, or lifecycle modeling. Experience with MLOps best practices, including model versioning, CI/CD for ML, monitoring, and operating models in containerized and orchestrated environments (Docker, Kubernetes). Experience in e-commerce, marketplace, or subscription-based businesses. Familiarity with working in environments with moderate technical debt or evolving data foundations. Experience defining and owning metrics, experimentation frameworks, or model performance monitoring in production. Demonstrated ability to influence beyond immediate project…
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