MiraiTech is a SportTech startup recognized for its achievements in various innovation competitions. AI platform for biomechanical analysis of athletes using proprietary sensors, scaling from R&D to production and commercial launch after securing a $700K Pre-Seed round.
• Full ML cycle: Experiment Design, Data Collection, Processing, Model Development, Validation, Deployment, Monitoring, Visualization
• Develop, train, validate, and deploy ML/DL models in production
• Work with Time Series and multimodal sensor data
• Improve accuracy, robustness, latency, and efficiency of models
• Build monitoring, versioning, and retraining pipelines
• Collaborate with hardware devices and sensors
• Participate in R&D, experimental design, and data collection
• Develop ML inference and data-processing services
• Work with APIs, databases, GPU, and cloud infrastructure
• Participate in ML/backend architecture design
• Set up AI Agents, LLM workflows, and integrations with external systems
• Provide technical leadership in ML
• Mentor engineers and develop ML engineering practices
• Develop, train, validate, and deploy ML/DL models in production
• Work with Time Series and multimodal sensor data
• Improve accuracy, robustness, latency, and efficiency of models
• Build monitoring, versioning, and retraining pipelines
• Collaborate with hardware devices and sensors
• Participate in R&D, experimental design, and data collection
• Develop ML inference and data-processing services
• Work with APIs, databases, GPU, and cloud infrastructure
• Participate in ML/backend architecture design
• Set up AI Agents, LLM workflows, and integrations with external systems
• Provide technical leadership in ML
• Mentor engineers and develop ML engineering practices
• 3+ years of commercial experience in Machine Learning
• Proficient in Python
• Practical experience with Deep Learning
• Strong experience with Time Series
• Experience with PyTorch / TensorFlow or similar frameworks
• Understanding of signal processing, statistics, and ML evaluation
• Experience deploying ML models in production
• Experience developing APIs and data pipelines
• Familiarity with Docker, databases, and cloud infrastructure
• Experience with GPU workloads
• Ability to independently drive ML tasks from experimentation to production
• Proficient in Python
• Practical experience with Deep Learning
• Strong experience with Time Series
• Experience with PyTorch / TensorFlow or similar frameworks
• Understanding of signal processing, statistics, and ML evaluation
• Experience deploying ML models in production
• Experience developing APIs and data pipelines
• Familiarity with Docker, databases, and cloud infrastructure
• Experience with GPU workloads
• Ability to independently drive ML tasks from experimentation to production
• IMU, pressure, force or biomechanical sensor data
• Wearables / IoT / Edge ML
• Signal Processing
• Computer Vision
• MLOps
• CUDA /
• Wearables / IoT / Edge ML
• Signal Processing
• Computer Vision
• MLOps
• CUDA /