ABOUT THE ROLE Reporting directly into the CIO organization, you will be the lead architect and "ace technologist" responsible for the next era of Peloton’s internal evolution: Agentic AI. You will go beyond simple chatbots to build autonomous and semi-autonomous AI agents that execute complex workflows across Finance, Supply Chain, Marketing, Legal, and the People Team. This role is for a hands-on coder who can also set the strategic technical roadmap for enterprise-wide automation. YOUR DAILY IMPACT AT PELOTON - Architect and code multi-agent systems that can reason, use tools, and execute end-to-end business processes (e.g., automated financial reconciliation, legal contract analysis, or supply chain demand forecasting) - Partner with leaders in Finance, Marketing, Legal, and HR to translate their complex operational challenges into concrete AI architectures - Evaluate the latest agentic frameworks and LLM providers to decide when to leverage third-party tools and when to build proprietary enterprise solutions - Design highly available inference services and manage model serving at scale, ensuring these agents integrate seamlessly with existing corporate service meshes - Implement "Security by Design," creating automated guardrails for PII/PHI filtering and mitigating prompt injection to ensure enterprise data remains secure - Optimize the "Total Cost of Ownership" by managing trade-offs between agent reasoning depth (latency) and compute costs through intelligent caching and specialized routing YOU BRING TO PELOTON - 8–10+ years in software engineering, with at least 2 years of deep focus on AI/ML infrastructure or data engineering at scale - Mastery of Python, Go, or Java/Scala, with a strong grasp of distributed systems and microservices - Proven experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and deep understanding of vector databases (e.g., Pinecone, Milvus, Weaviate) - Hands-on experience with modern data stacks (Spark, Kafka, Snowflake, Databricks) and cloud environments (AWS, GCP, or Azure) - Expert knowledge of Kubernetes, Docker, and CI/CD patterns specifically for machine learning lifecycles #LI-DD1 #LI-Remote The base salary range represents the low and high end of the anticipated salary range for this position to be performed remotely from any Peloton office or facility, in any U.S. State and any location therein. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives. Our base salary is just one component of Peloton’s competitive total rewards strategy that also includes annual equity awards and an Employee Stock Purchase Plan as well as other region-specific health and welfare benefits. As an organization, one of our top priorities is to maintain the health and wellbeing for our employees and their family. To achieve this goal, we offer robust and comprehensive benefits including: - Medical, dental and vision insurance - Generous paid time off policy - Short-term and long-term disability - Access to mental health services - 401k, tuition reimbursement and student loan paydown plans - Employee Stock Purchase Plan - Fertility and adoption support and up to 18 weeks of paid parental leave - Child care and family care discounts - Free access to Peloton Digital App and apparel and product discounts - Commuter benefits and Citi Bike Discount - Pet insurance and so much more! Base Salary Range $172,250—$240,350 USD ABOUT PELOTON: Peloton (NASDAQ: PTON) provides Members with expert instruction, and world class content to create impactful and entertaining workout experiences for anyone, anywhere and at any stage in their fitness journey. At home, outdoors, traveling, or at the gym, Peloton brings together innovative hardware, distinctive software, and exclusive content. Founded in 2012 and headquartered in New York City, Peloton has millions of Members across the US, UK, Canada, Germany, Australia, and Austria. For more information, visit www.onepeloton.com. Peloton is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. Equal employment opportunity has been, and will continue to be, a fundamental principle at Peloton, where all team members, applicants, and other covered persons are considered on the basis of their personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, or any other protected characteristic as established by applicable law. This policy of equal employment opportunity applies to all practices and procedures relating to recruitment and hiring, compensation, benefits, termination, and all other terms and conditions of employment. If you would like to request any accommodations from application through to interview, please email: applicantaccommodations@onepeloton.com. At Peloton, we embrace technology, including AI, to enhance productivity and accelerate innovation in the work we do for our members. However, in our hiring process, our priority remains in getting to know you and your unique qualifications. To ensure a fair and equitable process, we do not permit the use of AI tools during any stage of the application and interview process. In considering you as an applicant, we want to understand your skills, experiences, and motivations without mediation through an AI system. We also want to directly assess your communication skills without the use of an AI tool. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance and the San Francisco Fair Chance Ordinance, as applicable to applicants applying for positions in these jurisdictions. Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address. If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence. Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational chemistry problems that simulate real chemistry research workflows; - Create problems requiring Python programming to solve (using numpy, scipy, chemical libraries); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in physical chemistry, quantum chemistry, and molecular modeling; - Base problems on real research challenges or practical applications from chemistry practice; - Verify solutions using Python with standard computational chemistry approaches; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for chemistry specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Chemistry or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods in chemistry; - Familiarity with computational chemistry concepts and methods; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational chemistry problems that simulate real chemistry research workflows; - Create problems requiring Python programming to solve (using numpy, scipy, chemical libraries); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in physical chemistry, quantum chemistry, and molecular modeling; - Base problems on real research challenges or practical applications from chemistry practice; - Verify solutions using Python with standard computational chemistry approaches; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for chemistry specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Chemistry or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods in chemistry; - Familiarity with computational chemistry concepts and methods; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may:  - Design original computational chemistry problems that simulate real chemistry research workflows; - Create problems requiring Python programming to solve (using numpy, scipy, chemical libraries); - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); - Develop problems requiring non-trivial reasoning chains in physical chemistry, quantum chemistry, and molecular modeling; - Base problems on real research challenges or practical applications from chemistry practice; - Verify solutions using Python with standard computational chemistry approaches; - Document problem statements clearly and provide verified correct answers. What we look for This opportunity is a good fit for chemistry specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:   - Degree in Chemistry or related fields; - Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; - 2+ years of professional experience: applied, research, or teaching experience is applicable; - Experience with numerical methods in chemistry; - Familiarity with computational chemistry concepts and methods; - Strong written English (C1+). How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $76 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.