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Machine Learning EngineerPeKe LabsUnited States

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Machine Learning Engineer

PeKe Labs
  • US
    United States
  • US
    United States

Über

Overview
We're hiring our first ML Software Engineer to work alongside our cofounder, Thane Hunt, in developing our software stack to help interpret raw data s About Peke Labs Corp
We're building the next generation of technological controllers using proprietary and patent-protected technology that translates muscle movement into data. Role
Machine Learning Software Engineer About Us : We are a cutting-edge technology company focused on revolutionizing the way we interpret
raw tendonal and muscular data
into actionable technological outputs. Our goal is to empower industries and individuals with transformative software that bridges the gap between human motion and machine interaction. We’re a fast-paced, innovative team driven by curiosity, purpose, and a passion for creating real-world impact. We are looking for a
super nimble, self-directed Machine Learning Software Engineer
to join us in building the future of wearable tech and motion analytics. About the Role: As an ML Software Engineer, you’ll be responsible for designing and implementing advanced machine learning algorithms to process complex muscular and tendonal data and convert it into outputs. You’ll work at the cutting edge of biomechanics and wearable technology, creating software that empowers our devices to understand and interpret human motion in real time. What You’ll Do
Design and implement
machine learning models
to analyze raw datasets and translate it into actionable technological outputs. Collaborate closely with hardware and software engineers to integrate ML solutions into our software stack. Continuously optimize and improve the performance of our models, focusing on real-time data processing and reducing latency. Develop and test novel algorithms to ensure they meet the evolving needs of our product and industry. Take ownership of your projects from concept to deployment, balancing speed and accuracy to ensure timely delivery of working solutions. Engage in problem-solving and troubleshooting, keeping the team moving forward despite challenges or roadblocks. Contribute to a fast-paced, agile development process where
doing
is prioritized over perfection. Stay up to date on the latest advancements in machine learning, biomechanics, and wearable technology, and continuously innovate. Qualifications
Experience
in developing machine learning models, with a focus on real-time data processing. Solid programming skills
in Python, C++, or similar languages commonly used in machine learning environments. Proficiency with
ML libraries
(TensorFlow, PyTorch, etc.) and
data manipulation tools
(Pandas, NumPy, etc.). Experience with
sensor data
and working with raw data inputs from wearables or similar devices. Comfortable working in a
self-directed environment
with little supervision—your ability to prioritize and execute will set you apart. A
bias towards doing : You’re someone who gets things done, doesn’t wait for perfect conditions, and takes action to solve problems. A
growth mindset , excited to take on new challenges and innovate in a fast-moving environment. Excellent
communication skills
and a collaborative attitude, even when tackling complex technical problems. Nice-to-Haves
Experience with
biomechanics, kinesiology, or motion analysis . Familiarity with
real-time systems
and
edge computing . Knowledge of
motion capture technologies ,
wearable sensors , or
gesture recognition . Familiarity with
cloud platforms
and deploying ML models at scale. Why Join Us
Work at the intersection of
biomechanics ,
AI , and
wearable technology —help us shape the future of human-machine interaction. Be part of a
nimble, collaborative team
where every member’s voice is heard, and every contribution matters. Opportunities for
professional growth
and learning in an
innovative, fast-paced environment . Competitive
compensation
and
equity options
in a company and cofounders who prioritize communication and seeing the world outside the box.
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  • United States

Sprachkenntnisse

  • English
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