Machine Learning Engineer

Summary

PeKe Labs is a technology company developing controllers that translate muscular and tendonal movement into data and technological outputs. The Machine Learning Software Engineer will design and implement machine learning algorithms for real-time interpretation of muscular and tendonal data, integrate ML solutions into the software stack, and optimize models for wearable technology and motion analytics.

Responsibilities

• 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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

Benefits

• Opportunities for professional growth and learning in an innovative, fast-paced environment.
• Equity options