Role Description The Buyer Growth team is responsible for driving Whatnot’s top-of-funnel growth and first-time buyer success. We're looking for a Machine Learning Engineer to accelerate buyer growth at Whatnot through intelligent, data-driven experiences. As the first ML engineer, you’ll build and own ML models personalization in onboarding and user targeting in our acquisition and engagement channels. This is a high-impact role on a team directly responsible for growing Whatnot’s buyer base and improving first-time user conversion. - Lead the design, development, and productionization of ML models that power user acquisition, activation, and retention (e.g., ranking models, targeting systems, uplift modeling). - Own the full model lifecycle: from data collection and feature engineering to model training, evaluation, deployment, and online experimentation. - Identify and prioritize high-impact opportunities where machine learning can unlock growth, collaborating with product, engineering, data, and marketing stakeholders. - Drive technical excellence and establish ML best practices across the Buyer Growth team. Qualifications - 5+ years of industry experience building and deploying ML systems at scale. - Demonstrated success in leading end-to-end ML projects that drove measurable business outcomes. - Deep expertise in personalization, ranking, or user modeling; strong intuition around user behavior in consumer products. - Advanced proficiency in Python, SQL, and common ML frameworks (e.g., PyTorch, TensorFlow, XGBoost). - Strong communication and leadership skills; ability to influence roadmap and align cross-functional teams. Requirements - Experience building ML applications in E-commerce or Social products. - Prior experience in growth domains: user segmentation, retention modeling, large scale recommendation systems, notification ranking, etc. Benefits - Flexible Time off Policy and Company-wide Holidays (including a spring and winter break). - Health Insurance options including Medical, Dental, Vision. - Work From Home Support. - Home office setup allowance. - Monthly allowance for cell phone and internet. - Care benefits. - Monthly allowance for wellness. - Annual allowance towards Childcare. - Lifetime benefit for family planning, such as adoption or fertility expenses. - Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally. - Monthly allowance to dogfood the app. - Parental Leave: 16 weeks of paid parental leave + one month gradual return to work (company leave allowances run concurrently with country leave requirements which take precedence).

• Designing model evaluation pipelines for models in development and production • Designing user studies for subjective model evaluations. • Converting requirements into measurable metrics. • Designing and developing automated evaluation dashboard to see model performances and compare results. • Training new models to capture new and different evaluation metrics. • Communicating with the model team to help design better models based on the evaluation results. • Communicating with the data team to help decide the type of data necessary to improve model performance. • Communication with the product-manager to make sure product requirements are correctly measured. • Help grow the evaluation team as the founding member. • Lead the evaluation team in the future.

• Own ML Data Collection & Incubation Programs • Define and scope complex operational challenges into clear, actionable workstreams with measurable success criteria • Plan and execute data collection programs that feed Dandy's highest-priority ML initiatives • Monitor project health, measure operational efficiency, and flag implementation risks • Synthesize updates into clear status reports that drive alignment and keep projects on track • Build ML Workforce Enablement Programs • Design and lead training programs that upskill our manufacturing and DDC workforce on ML-related tools, workflows, and expectations • Own the full cycle from needs assessment through delivery and iteration, and adjust quickly when something isn't working • Stand Up Model Testing Infrastructure • Build the operational framework for testing new ML models in a live workforce environment • Define success criteria, coordinate across Operations and Quality teams, and create the reporting that makes model performance visible to decision-makers • Drive Stakeholder Alignment • Develop and maintain detailed project plans to monitor progress against milestones and deliverables • Build coalitions of support across teams including ML, Operations, Quality, and People • Communicate clearly across multiple levels and cultural contexts

Role Description The Cornell Lab of Ornithology is seeking a creative, mission-driven Machine Learning Software Engineer to join the team that develops machine learning models incorporated into Merlin Bird ID, a mobile app that helps millions of people worldwide identify birds using automated detection and classification of birds in images, audio, and video. This role will join a team that shares the mission of connecting people to nature and conservation through birds. As part of a team of software engineers, content creators, machine learning researchers, and conservation scientists, this role will be critical to integrate machine learning models into products for a global community of birders, researchers, and conservation practitioners. The Machine Learning Software Engineer will be expected to: - Engage in software engineering projects with multiple, concurrent development efforts. - Interact with both internal and external collaborators and architect application solutions. - Develop production applications. - Serve as a technical liaison between internal engineering teams, supporting coordination and integration of application infrastructure to meet strategic objectives. - Participate actively in the design and evolution of CLO technical systems, including the integration of machine learning research into production systems. Qualifications - Bachelor’s degree in Computer Science and three (3)+ years of relevant experience or equivalent combination of education and experience. - Experienced in machine learning and software development in research and production environments. - Extensive Python experience, including knowledge of numpy, pandas, Tensorflow and/or Pytorch. - Extensive experience working with large numerical and audiovisual datasets in Python. - Extensive Linux command line experience. - Experience with AWS, GCP, or Azure. - Experience with databases, both SQL and non-SQL. - Experience developing and integrating with APIs and web services. - Demonstrated experience in managing complex information technology projects. - Experience defining project requirements, including hardware and software. - Experience using software development, deployment and project management tools. - Strong problem-solving and critical thinking skills. - Excellent written and oral communication skills. - Ability to clearly communicate complex technical issues to leadership team. - Ability to work both independently and collaboratively. - Must be able to handle multiple concurrent tasks and priorities. - Experience in and/or demonstrated commitment to supporting diversity, equity, access, inclusion, and wellbeing. - Demonstrated skill in understanding of cultural differences. Requirements - Advanced degree preferred with publications in the fields of computer vision, machine learning, or similar. - More than seven (7) years’ experience. - Prior use and thorough understanding of Merlin, eBird, or other Cornell Lab tools and resources. - Understanding of and interest in conservation, birds, bird monitoring protocols, and related vocabulary. - Experience with enterprise components: web servers (e.g., Apache HTTP Server), Java application servers (e.g., Apache Tomcat), content management systems (e.g., WordPress), servers providing GIS functionality (e.g., GeoServer), relational databases (e.g., Postgres), single sign-on systems, LDAP servers, automation servers (e.g., Jenkins), analytics and user tracking (e.g., Firebase, HubSpot). - Knowledge of security issues, disaster recovery, monitoring, virtualization, cloud infrastructure, and enterprise storage technologies. - Experience writing grants and seeking external funding to support technical infrastructure. Benefits - Comprehensive health care options. - Generous retirement contributions. - Access to wellness programs. - Employee discounts with local and national retail brands. - Health and personal leave, three weeks of vacation, and 13 holidays. - Tuition-free Extramural Study and Employee Degree Program. - Tuition aid for external education. - Cornell Children's Tuition Assistance Program.