Machine Learning Engineer

We are looking for a Movement Detection ML Engineer to drive the research and development of exercise-recognition models from IMU sensor data (accelerometer/gyroscope) and scale coverage from our current ensemble to several hundred exercises, while taking inference live on-device.

Responsibilities:

• Increase accuracy and expand coverage to several hundred exercises. You will fine-tune existing models, redesign ensembling strategies, evaluate architectures suited for long-tail, imbalanced multi-class time-series classification, and adapt training regimes (data augmentation, sampling, curriculum learning) for newly annotated data.

• Port the server-side inference pipeline to run live on iOS/Android devices under strict latency, memory, and compute constraints, handling real-world sensor noise and dropped samples through model export, quantization, and distillation.

• Ensure all architectural and ensembling wins on offline accuracy respect mobile edge-budget constraints right from the design phase.

Requirements:

• Hands-on experience around 5 years with PyTorch and PyTorch Lightning for building, training, and extending production pipelines, along with Python proficiency.
• Strong applied deep learning background grounded in numerical/signal time-series data (IMU, EMG, audio, sensor fusion, biosignals, or industrial time-series) using architectures such as 1D-CNNs, RNNs/GRUs, dilated convolutions, or Temporal Transformers.
• Comfortable with ensembling and cascade-style model architectures — combining multiple models’ outputs and evaluating latency/complexity vs. performance trade-offs.
• Solid grasp of evaluation metrics for imbalanced, multi-class time-series classification/segmentation across hundreds of classes (precision/recall trade-offs, label noise, sensor placement variance).
• Able to work independently with a large, configuration-driven codebase, respecting established architectural conventions and software design patterns.
• Strong Upper-Intermediate (B2+) or higher — comfortable with daily written and spoken technical communication.
• Working hours are from 15:00 to 23:00 to ensure team alignment.

Nice to have:

• Experience with AWS Batch, Step Functions, S3, and Docker containerization for scalable model training.
• On-device/edge inference: CoreML, TFLite, ONNX Runtime Mobile, or similar export/runtime experience.
• Model compression: quantization, pruning, distillation.
• Wearables or human activity recognition (HAR) experience specifically.
• Weights & Biases or comparable experiment-tracking discipline.
• Mobile app-side familiarity (Swift/Kotlin).
  
  
  

What you will have with us:

• Paid out of office days;
• Regular Performance review;
• Company-funded learning & development opportunities;
• Flexible work schedule;
• Well-equipped office;
• Career Path and growth opportunities.

About the company Kevych Solutions

We are a software development company that provides digital technology services from mobile and web development to custom software solutions. We’re dedicated to delivering innovative, high-quality solutions tailored to your unique needs.

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