• Design, develop, and optimize machine learning models in one or more solutions, including asset generation and capture, render enhancement, scene intelligence, agentic design workflows, and intuitive design interactions. • Investigate and bring techniques from a variety of AI research areas, such as diffusion, super-resolution, conditioned generation, plus neural and differentiable rendering, into artists’ hands. • Evaluate, integrate, and orchestrate off-the-shelf third-party foundation models to accelerate feature development and deployment. • Mentor other engineers and contribute to the growth of the team’s knowledge and expertise in machine learning. • Collaborate with cross-functional teams and our ML Product Manager to define the product requirements and scope of delivery of solutions to product teams. • Work closely with our MLOps Engineer to develop and maintain pipelines for distributed training, inference optimization/quantization/serving, experiment tracking, model versioning & validation, and deployment to the cloud (AWS/Azure/GCP). • Implement appropriate model evaluation tests, data curation processes, and apply dataset-rights awareness, and responsible AI/governance. • Stay updated and share knowledge on the latest developments in machine learning, generative AI, natural language processing, and 3D visualization, and implement cutting-edge techniques to enhance our solutions. • Ensure high-quality code and documentation, following best practices in software development and machine learning.

• Design, develop, and optimize scalable Machine Learning models for advertising intelligence and forecasting systems • Analyze large-scale historical and real-time datasets to improve forecasting accuracy and monetization strategies • Build and maintain distributed data processing pipelines using Spark and related Big Data technologies • Develop production-ready ML solutions using Python within AWS cloud infrastructure • Research, evaluate, and implement Machine Learning algorithms suitable for high-load AdTech environments • Improve model performance, scalability, reliability, and operational efficiency • Collaborate with Data Engineers, Product Managers, and distributed engineering teams to deliver end-to-end ML solutions • Contribute to ML architecture decisions, experimentation approaches, and engineering best practices • Monitor, validate, and optimize ML model quality and forecasting performance in production environments • Produce technical documentation related to ML pipelines, models, and distributed systems • Mentor engineers and support technical growth within the team • Drive innovation in Machine Learning and AdTech technologies

• Design, develop, and optimize scalable Machine Learning models for advertising intelligence and forecasting systems • Analyze large-scale historical and real-time datasets to improve forecasting accuracy and monetization strategies • Build and maintain distributed data processing pipelines using Spark and related Big Data technologies • Develop production-ready ML solutions using Python within AWS cloud infrastructure • Research, evaluate, and implement Machine Learning algorithms suitable for high-load AdTech environments • Improve model performance, scalability, reliability, and operational efficiency • Collaborate with Data Engineers, Product Managers, and distributed engineering teams to deliver end-to-end ML solutions • Contribute to ML architecture decisions, experimentation approaches, and engineering best practices • Monitor, validate, and optimize ML model quality and forecasting performance in production environments • Produce technical documentation related to ML pipelines, models, and distributed systems • Mentor engineers and support technical growth within the team • Drive innovation in Machine Learning and AdTech technologies

Role Description The Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems and platforms that make an impact on millions of users. This role will work closely with business partners to provide machine intelligence driven solutions and products to simplify and enhance the customer experience and to automate core business processes. The Machine Learning Engineer will partner closely with Data Scientists, Applied Scientists, and Software Developers to ensure predictive models make business impact. Job Expectations - Partner with the Data Platform team in a two-way exchange of best practices. - Adopt common patterns and build effective abstractions across different machine learning pipelines that simplify existing machine learning processes and accelerate the modelling process from the business problem’s inception to deploying a model solution into production. - Develop horizontal solutions to robustly scale the team’s machine learning models and processes. - Build software with Object-oriented Design Patterns and Analysis (OOA and OOD) with an eye toward reducing technical debt and maintaining services at high availability. - Participate in requirements reviews, design reviews, and code reviews. - Research and prototype new technologies to support the rapid growth of the business. - Interact cross-functionally with a wide variety of technical teams and work closely with data and applied scientists to identify opportunities to improve on iHerb’s platform. Qualifications - Strong coding experience (e.g. Java, C#, Python). - Experience with gathering data from multiple sources using big data technologies (Spark, Hadoop, BigQuery, Athena, etc.). - Experience building machine learning infrastructure following robust software engineering practices. - Knowledge of modern software development tools, systems, and practices (design patterns, CI/CD, git, unit testing, smoke testing, integration testing, job schedulers, cloud technologies like AWS Lambdas and Google functions, etc.). - Exposure to all aspects of the software development life-cycle. - Experience with messaging technologies (Kafka, Google Pub/Sub, Kinesis, RabbitMQ, etc.). - Experience with Docker and Kubernetes. - High degree of accuracy and attention to detail. - Excellent organization skills and ability to multitask. Experience Requirements - Generally requires a minimum of two (2) years relevant experience in applied machine learning or machine learning systems/infrastructure. - One (1) year of relevant work experience in machine learning engineering or related fields (e.g., as a Machine Learning Engineer, ML Ops engineer, or related position). Education Requirements - Bachelor’s Degree in Computer Science, Electrical Engineering, or related field required. - Masters Degree preferred. Judgment/Reasoning Ability Able to identify, troubleshoot and resolve problems quickly using sound judgment, poise and diplomacy. Ability to use judgment and reasoning skills, and determine when to escalate issues, as required, in a timely manner. Physical Demands The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job. While performing the duties of this job, the Team Member is regularly required to talk and hear. The Team Member is frequently required to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach with hands and arms. Reaching above shoulder heights, below the waist or lifting as required to file documents or store materials throughout the work day. The Team Member may occasionally lift or move office products and supplies up to 25 pounds. Proper lifting techniques required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work Environment - The noise in the work environment is usually moderate. - Hectic, fast-paced with multi-level distractions. - Professional, yet casual work environment. - Office / Warehouse environment. - Ability to work extended hours as required. Compensation The expected salary range for this role is $205,000.00 - $230,000.00 USD. The actual base pay offered will be determined by factors such as the candidate's relevant experience, education, geographic location, and internal equity. Staffing Agency Submission Notice iHerb does not accept unsolicited 3rd party ("Agency") candidates. If you are an Agency, please send any requests to be considered as a supplier in our Vendor Management System to staffingvendors@iherb.com. Do not contact iHerb employees directly. If requested to work on a role, any Agency candidates would be presented through the internal recruiting organization. Equal Opportunity Employer iHerb is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. iHerb provides equal employment opportunities to all applicants for employment and prohibits discrimination and harassment.