Machine Learning Engineer, NLP/NLU

ABOUT THE ROLE Peloton is looking for a Machine Learning Engineer to develop natural language processing capabilities for connected fitness. Your main focus will be to enhance the existing NLP/NLU platform with the help of the latest machine learning techniques and tools. The Content AI team applies AI/ML to enhance Peloton’s fitness content, as part of the team you will be working on voice transcription and translations pipelines, search and discovery algorithms, Generative AI and voice assistance technology. YOUR DAILY IMPACT AT PELOTON Work with the rest of the team to solve problems in the NLP/NLU domain such as named entity recognition, user intent recognition, query classification, etc. Work to build/train/deploy open source models such as Whisper, LLaMA, etc. Hypothesize, design and conduct various experiments in the natural language processing, understanding and generation domain. Provide help to build tools to mine and label text datasets for training/testing. Work on search algorithms/optimizations using OpenSearch/Elastic Search. YOU BRING TO PELOTON Masters in Machine Learning, AI, Computer Science, Mathematics, etc. 1-2 years of experience developing solutions using supervised and unsupervised machine learning techniques in natural language processing applications. Understanding of transformer models, GenAI including few shot learning, fine tuning, guardrailing and benchmarking, etc. Understanding of various neural network architectures specifically applied to solve NLP problems, such as CNN/LSTM/GRU and transformer based architectures. Should have a deep understanding of word embeddings, BERT, GPT, text classifiers, transfer learning, text mining and text labeling concepts. Experience with multiple technologies from the following list: Tensorflow, PyTorch, spaCy, Sagemaker, MLFlow, Airflow, TensorBoard, Anaconda, Jupyter, Kubernetes. Experience with building personal digital assistants or chatbots. Experience with building search platforms, personalizing search and discovery. Worked with automatic speech recognition (ASR). COMPENSATION AND BENEFITS The base salary range represents the low and high end of the anticipated salary range for this position based at our New York City headquarters. The actual base salary offered for this position will depend on numerous factors including individual performance, 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 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! 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 immersive classes, cutting-edge technology and hardware, and the Peloton App with multiple tiers to personalize the Peloton experience [with or without equipment]. 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. At Peloton, we motivate the world to live better. “Together We Go Far” means that we are greater than the sum of our parts, stronger collectively when each one of us is at our best.

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