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.

Role Description Analytical Mechanics Associates (AMA) is seeking a highly specialized Subject Matter Expert to serve in a part-time, advisory capacity. This consultant will provide strategic technical guidance and expert review at the intersection of computational aerothermodynamics, advanced modeling and simulation (M&S), and machine learning (ML). Requiring a commitment of no more than 20 hours per month, this role is ideal for an established researcher, academic, or industry veteran looking to lend their expertise to cutting-edge aerospace challenges without a full-time commitment. The hourly rate for this position is $59-$69 an hour commensurate with experience and education. Key Responsibilities - Technical Advisory: Provide expert-level consultation on computational aerothermodynamics methodologies, physics-based modeling, and simulation strategies. - Machine Learning Integration: Advise on the application and integration of machine learning algorithms (e.g., surrogate modeling, physics-informed neural networks, data-driven turbulence modeling) to enhance traditional CFD and aerothermodynamic workflows. - Design & Architecture Review: Evaluate and provide feedback on the architecture of high-performance physical models and numerical methods. - Strategic Roadmapping: Assist engineering teams in identifying emerging trends and state-of-the-art techniques in M&S and computational physics to maintain a competitive technical edge. - Mentorship & Collaboration: Serve as a sounding board for senior engineers and developers, helping to troubleshoot complex physical and algorithmic challenges. Qualifications - Education: Ph.D. in Aerospace Engineering, Mechanical Engineering, Physics, or a strictly related computational discipline. - Experience: A minimum of 5 years of active, post-Ph.D. professional experience specifically focused on computational aerothermodynamics, M&S, and ML. - Domain Expertise: Deep foundational knowledge of hypersonic and supersonic flows, high-temperature gas dynamics, and advanced computational fluid dynamics (CFD). - Machine Learning Proficiency: Proven track record of applying machine learning, deep learning, or advanced statistical modeling to complex fluid dynamics or thermodynamic problems. - Communication: Exceptional ability to distill complex theoretical concepts into actionable engineering guidance. Preferred Qualifications - Familiarity with modern, high-performance software architecture, particularly the development of robust C++ libraries for CFD codes (e.g., providing complex gas properties). - Experience with heterogeneous computing environments, including GPU acceleration and parallel programming models (e.g., OpenMP, CUDA, Kokkos). - Deep knowledge of physics of high-enthalpy flows, including thermal radiation, chemical kinetics, and transport processes. - History of peer-reviewed publications in relevant aerospace, physics, or computational science journals. Requirements - This position requires U.S. Citizenship or Permanent Residence. Benefits - Competitive salaries. - Substantial benefits package, including but not limited to: - Paid personal and federally recognized holiday leave. - Salary deferrals into a 401(k)-matching plan with immediate vesting. - Tuition reimbursement. - Short/long term disability plans. - A variety of medical, dental, and vision insurance options.

• Build and operate production-grade model serving infrastructure using frameworks such as vLLM, TGI, Triton, or equivalent • Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models • Develop and maintain auto-scaling systems, multi-model serving architectures, and intelligent request routing layers • Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance • Design observability systems for tracking inference latency, throughput, GPU usage, cost metrics, and system health • Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments • Own the full lifecycle of ML systems from development through production, including operational support and on-call responsibilities • Define engineering best practices and contribute to platform scalability in a fast-moving startup environment

Role Description This job entails directing advanced machine learning projects for decision automation and pattern recognition. It includes setting goals, designing prototypes, and leading research. The role manages sophisticated solutions, authors critical documentation, and mentors engineers. High-level machine learning expertise and innovation capacity are essential. Responsibilities - Leading the development of machine learning programs to identify patterns and automate decision-making processes - Setting technical objectives for machine learning assignments and overseeing their execution - Designing machine learning prototypes in collaboration with product teams and stakeholders - Conducting research and studies to inform product development and application of machine learning techniques - Implementing end-to-end machine learning solutions, including optimization technologies, and managing live deployments - Aggregating and analyzing data from multiple sources to discover patterns for feature engineering and model automation - Authoring technical documentation, including white papers and technical manuals, and contributing to intellectual property with patents and APIs - Evaluating machine learning solutions from internal and external partners, conducting case studies and reporting on outcomes - Collaborating with external teams and representing the work group in resolving technical challenges related to machine learning projects - Mentoring junior engineers in machine learning methodologies and leading by example in technical expertise and innovation - Consistent exercise of independent judgment and discretion in matters of significance - Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) as necessary - Other duties and responsibilities as assigned Expectations - Understand our Operating Principles; make them the guidelines for how you do your job - Own the customer experience think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services - Know your stuff be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences - Win as a team make big things happen by working together and being open to new ideas - Be an active part of the Net Promoter System a way of working that brings more employee and customer feedback into the company by joining huddles, making call backs and helping us elevate opportunities to do better for our customers - Drive results and growth - Support a culture of inclusion in how you work and lead - Do what's right for each other, our customers, investors and our communities Qualifications - Bachelor's Degree (preferred) - 7-10 Years of relevant work experience - Possessing a combination of coursework and experience, or extensive related professional experience may be considered Skills - Agentic AI - Agentic Orchestration - Customer Experience (CX) - Generative AI Agents - Machine Learning (ML) Compensation - National Pay Range: $117,098.24 USD - $274,449.00 USD - Illinois Pay Range: $124,416.88 USD - $241,515.12 USD - Colorado Pay Range: $131,735.52 USD - $252,493.08 USD - Hawaii Pay Range: $153,691.44 USD - $230,537.16 USD - Washington DC Pay Range: $168,328.72 USD - $252,493.08 USD - Maryland Pay Range: $139,054.16 USD - $252,493.08 USD - Minnesota Pay Range: $131,735.52 USD - $230,537.16 USD - New York Pay Range: $139,054.16 USD - $274,449.00 USD - Washington Pay Range: $131,735.52 USD - $263,471.04 USD - New Jersey Pay Range: $146,372.80 USD - $263,471.04 USD - Vermont Pay Range: $139,054.16 USD - $219,559.20 USD - Massachusetts Pay Range: $146,372.80 USD - $263,471.04 USD - California Pay Range: $131,735.52 USD - $243,954.66 USD Disclaimer This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.