Job Description

Join to apply for the Senior Machine Learning Engineer role at Peloton Interactive Join to apply for the Senior Machine Learning Engineer role at Peloton Interactive Get AI-powered advice on this job and more exclusive features. Direct message the job poster from Peloton Interactive

ABOUT THE ROLE

This role is hybrid in New York City or the Bay Area! The AI/CV team is working on powering products that incorporate computer vision into the fitness domain. We are looking for a Senior Machine Learning Engineer, Deployment focused on Deep Learning/Computer Vision. The role will involve working closely with ML and Systems Engineers to ensure the success of ML applications on device, defining processes for packaging and deploying ML projects, and guiding the team on best practices for managing multi-dependency modules. Responsibilities Collaborate and work closely with engineers to translate and deploy new AI/ML solutions for connected fitness devices. Be the voice in the room that guides development work by ensuring work being done by the team is deployable in an end to end system. Ensure model performance remains within expected bounds when promoting experimental models to production. Specifically, you may encounter projects focused on: Temporal modeling, Object Detection, Segmentation, Perception, Multi-modal and Ensembling Qualifications Hands-on, real-world experience with one or more of Computer Vision, Machine Learning, Deep Learning. Must have proficiency in C/C++ and Python Proficiency in ML frameworks like PyTorch, Tensorflow, Keras, etc. Ability to quickly translate research work into high-quality production code with a strong sense of good system design. Deep understanding of various neural network architectures specifically applied to solve CV problems, such as CNN/LSTM/3DConvs/GNN/TCN/Metric Learning and transformer based architectures. Comfortable working with large image and video datasets. Experience working in a CI/CD environment and git Excellent written and verbal communications skills. Bonus Points Experience with one or more of: Hands on experience on Model Compression techniques such as Quantization, Pruning, Distillation Experience with one of the following frameworks: Qualcomm SNPE, Tensorflow Lite, CoreML or other similar Edge Inference/NN Acceleration frameworks. Experience developing software for consumer products on Mobile SoCs, within the Android NDK framework and/or using CoreML for iOS. Experience developing Deep Learning models, especially for Detection, Tracking, Sequential modeling, Transformers and Few-Shot Learning tasks. Experience with compute offloads to GPU, DSPs, etc. Experience with profiling and tracing tools. Experience with Objective-c, Swift The base salary range represents the low and high end of the anticipated salary range for this position based at our Santa Clara office. The actual base salary offered for this position will depend on numerous factors including, without limitation, experience and business objectives and if the location for the job changes. 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 insuranceGenerous paid time off policyShort-term and long-term disabilityAccess to mental health services401k, tuition reimbursement and student loan paydown plansEmployee Stock Purchase PlanFertility and adoption support and up to 18 weeks of paid parental leaveChild care and family care discountsFree access to Peloton Digital App and apparel and product discountsCommuter benefits and Citi Bike DiscountPet insurance and so much more! Base Salary Range: $200,750 USD - $246,600 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 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 andyour 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. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Wellness and Fitness Services Referrals increase your chances of interviewing at Peloton Interactive by 2x Get notified about new Senior Machine Learning Engineer jobs in Santa Clara, CA . Palo Alto, CA $162,800.00-$203,500.00 2 weeks ago Senior Prediction and Planning Machine Learning Engineer - Autonomous Vehicles Santa Clara, CA $184,000.00-$356,500.00 3 days ago Senior/ Principal Machine Learning Engineer Redwood City, CA $250,000.00-$400,000.00 1 week ago Senior Machine Learning Engineer - Data Gen AI team Sunnyvale, CA $198,000.00-$220,000.00 5 days ago Mountain View, CA $161,500.00-$219,000.00 6 days ago Machine Learning Software Engineer (SMTS) Santa Clara, CA $192,000.00-$288,000.00 4 hours ago Senior Machine Learning Engineer, Applied ML San Jose, CA $142,700.00-$257,600.00 1 week ago Senior Machine Learning Engineer – End-to-End Autonomous Driving Menlo Park, CA $173,000.00-$264,500.00 20 hours ago Palo Alto, CA $162,800.00-$203,500.00 4 hours ago San Jose, CA $142,700.00-$257,600.00 2 weeks ago Senior Machine Learning Engineer – End-to-End Autonomous Driving San Jose, CA $142,700.00-$257,600.00 5 days ago Senior Machine Learning Engineer, Recipe Pathfinding Senior Machine Learning Engineer - Marketplace Pricing Sunnyvale, CA $198,000.00-$220,000.00 3 weeks ago San Jose, CA $182,900.00-$334,500.00 3 days ago Senior Machine Learning Performance Engineer San Francisco Bay Area $200,000.00-$240,000.00 1 year ago Senior Machine Learning Research Scientist Senior Machine Learning Ops Engineer, GenAI Palo Alto, CA $162,800.00-$203,500.00 3 hours ago San Jose, CA $162,000.00-$301,200.00 2 weeks ago (USA) Senior, Software Engineer (Machine Learning) Sunnyvale, CA $117,000.00-$234,000.00 1 week ago Senior Machine Learning Software Engineer Senior Machine Learning Engineer, Prediction Mountain View, CA $204,000.00-$259,000.00 6 days ago Senior, Software Engineer (Machine Learning) Sunnyvale, CA $117,000.00-$234,000.00 1 week ago Senior Machine Learning Engineer, Simulation Realism San Jose, CA $142,700.00-$257,600.00 6 hours ago Mountain View, CA $200,000.00-$275,000.00 6 days ago Pleasanton, CA $167,200.00-$297,600.00 2 weeks ago San Jose, CA $146,800.00-$244,700.00 2 weeks ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr Peloton Interactive

Job Tags

Full time, Work at office, Local area,

Similar Jobs