Staff Applied Scientist (Human Performance AI)

As a Staff Applied Scientist (Human Performance AI) at Tonal, your primary responsibilities include designing and building advanced machine learning models and algorithms that enhance personalized training and improve user engagement. You will analyze movement patterns to identify fatigue and inefficiencies, thereby helping to refine training effectiveness. Additionally, you'll prototype and produce models that enrich our coaching capabilities and optimize the user experience, collaborating closely with various teams to implement new features.

To qualify for the Staff Applied Scientist role at Tonal, candidates should have 7+ years of experience in applied machine learning or data science, or 5+ years with a Master’s degree, or a PhD with 3+ years of relevant experience. A strong background in modeling time-series data particularly in the context of human motion or physical sensor data is essential. Proficiency in Python and familiarity with ML frameworks like PyTorch or TensorFlow is also required.

In the Staff Applied Scientist position at Tonal, you will be involved in exciting projects that focus on leveraging machine learning to enhance fitness technology. This includes creating algorithms that personalize workouts, assess user performance, and determine fatigue levels through real-world sensor data. You will also delve into defining new metrics for training effectiveness, applying self-supervised learning, and collaborating with diverse teams on innovative product features.

For a successful career as a Staff Applied Scientist (Human Performance AI) at Tonal, personal qualities such as being self-driven and passionate about real-world application of machine learning are vital. You should also possess excellent communication skills, as you'll need to simplify complex models for product audiences. An aptitude for collaboration in cross-functional teams, alongside the ability to experiment and iterate effectively, will contribute significantly to your success in this role.

While not mandatory, having a background or interest in fitness, performance training, or personalized coaching can significantly enhance your perspective and effectiveness in the Staff Applied Scientist (Human Performance AI) role at Tonal. Familiarity with biomechanics or sports science can also provide valuable insights that help shape our AI algorithms to serve users more effectively.

When answering this question, focus on specific projects where you took the lead, detailing the problem you aimed to solve, the models you developed, and the impact of your work. Discuss technologies you utilized and emphasize how the project contributed to user experience or product effectiveness.

Discuss your methodology for analyzing complex datasets by outlining your steps from data cleaning to model training. Explain your tools and techniques, such as statistical analysis or visualization, illustrating how you ensure accuracy and extract actionable insights.

When addressing this question, explain the algorithms or metrics you use to detect fatigue, such as analyzing patterns in sensor data. Share any previous experiences where you've successfully implemented your strategies and the results you achieved.

When responding, highlight a specific project where you utilized PyTorch or TensorFlow. Talk through the objectives, how you implemented the framework, and the results, making sure to emphasize the learning and growth that came from it.

Answer this question by discussing practices for continuous validation and model retraining based on new data. Illustrate with examples where you've implemented such practices effectively to maintain the performance and reliability of your models.

Share your vision for mentorship by discussing your preferred approach, whether it's conducting regular check-ins, providing resources, or facilitating hands-on project experience. Emphasize the importance of fostering a collaborative and open learning environment.

When answering, propose novel metrics that could enhance monitoring of user performance or training quality. Discuss any research or theories supporting your ideas and how these metrics could be implemented in Tonal's system.

Explain your approach to staying informed, whether through attending conferences, reading scholarly articles, or following influential figures in the field. Highlight specific resources you find particularly valuable and how you apply new knowledge to your work.

Discuss your conflict resolution approach by emphasizing active listening, finding common ground, and fostering a collaborative dialogue. Share a specific experience where you successfully navigated a similar situation.

When responding, share your personal connection to fitness technology and the impact it can have on users' lives. Discuss your enthusiasm for innovations in this field and how you hope your role at Tonal will contribute to advancing these technologies.