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Staff Machine Learning Engineer

Tonal

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Location:
United States , San Francisco ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

200000.00 - 235000.00 USD / Year
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Job Description:

Tonal is looking for a Staff Machine Learning Engineer to help expand Tonal’s intelligence across movements, training modalities, and member goals. You’ll be joining a high impact team at the intersection of machine learning, biomechanics, and product engineering. You will be responsible for building intelligent systems that adapt workouts, enhance coaching, and personalize progression using the largest strength training dataset in the world.

Job Responsibility:

  • Design, implement, and optimize machine learning training pipelines and model serving infrastructure for real time applications
  • Develop algorithms and ML models that enable personalized training, adaptive coaching, and performance prediction
  • Fine tune and evaluate transformer based or self supervised learning models using Tonal’s multimodal dataset
  • Build data driven systems that measure training effectiveness, effort, and progression beyond traditional weight based metrics
  • Prototype, train, and deploy ML models that run efficiently at scale or on device
  • Collaborate cross functionally with Exercise Science, Product, and Software teams to deliver intelligent features that improve the member experience
  • Contribute to the development of automated tools for experimentation, model validation, and continuous retraining
  • Write high quality, maintainable Python code and work closely with backend engineers to integrate models into Tonal’s production systems
  • Mentor teammates and help shape Tonal’s growing AI and ML best practices

Requirements:

  • 7 plus years of experience in software engineering or applied ML
  • 5 plus with a Master’s degree
  • PhD with 3 plus years of experience
  • Strong coding skills in Python
  • Experience with frameworks such as PyTorch, TensorFlow, or JAX
  • Experienced in ML training, evaluation, and deployment workflows such as Sagemaker, MLFlow, Databricks, or similar
  • Deep understanding of time series modeling, human motion, or sensor based learning from devices such as force transducers, position encoders, IMUs, or cameras
  • Familiar with MLOps best practices and scalable model training pipelines
  • Strong communicator who can collaborate with scientists, product managers, and engineers
  • Track record of delivering performant ML systems from prototype to production

Nice to have:

  • Experience fine tuning large transformer or multimodal models
  • Experience deploying models to real time or edge environments such as on device inference
  • Experience with GoLang, Kotlin or Flutter
  • Experience with distributed training, mixed precision optimization, or model compression
  • Interest in fitness, digital health, or intelligent training systems
  • Background in biomechanics, kinesiology, or human performance analytics
What we offer:
  • Offers Equity
  • Health insurance
  • Retirement savings benefits
  • Life insurance
  • Disability benefits
  • Flexible paid time off
  • Parental leave
  • Other additional benefits (location dependent)

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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