Deep Learning Engineer
Rapsodo
Deep Learning Engineer
Rapsodo
Provides data-driven performance analysis for athletes
Rapsodo · Ankara, Turkey · Full-time · Posted 2026-08-03
Workplace: on_site
Department: RDO
Rapsodo is a sports technology company that designs computer vision and machine learning products to help athletes maximize their performance. With offices strategically located in Singapore, Turkey, the USA, Japan, and the UK. Rapsodo is the undisputed leader in sports technology. Current partners include all 30 MLB teams, MLB, USA Baseball, Golf Digest, PGA of America, and over 1000 NCAA athletic departments.
Opened in 2018, our Turkey office operates as the R&D arm of Rapsodo. We have offices located in Bayraklı & Technopark in the Izmir Ege University, recognized by the Ministry of Science, Industry and Technology as one of Turkey’s most successful Technoparks. Our offices incorporate UI/UX, Mobile, Cloud Technologies along with Computer Vision, Deep Learning, Data Science and Unity teams. Rapsodo is rapidly growing, and we are looking for team players who will contribute to deliver state-of-the-art solutions with us.
We're looking for a Deep Learning Engineer to join our Computer Vision & Machine Learning team!
Description
Rapsodo is a sports technology company that designs computer vision and machine learning products to help athletes maximize their performance. With offices strategically located in Singapore, Turkey, the USA, Japan, and the UK. Rapsodo is the undisputed leader in sports technology. Current partners include all 30 MLB teams, MLB, USA Baseball, Golf Digest, PGA of America, and over 1000 NCAA athletic departments.
Opened in 2018, our Turkey office operates as the R&D arm of Rapsodo. We have offices located in Bayraklı & Technopark in the Izmir Ege University, recognized by the Ministry of Science, Industry and Technology as one of Turkey’s most successful Technoparks. Our offices incorporate UI/UX, Mobile, Cloud Technologies along with Computer Vision, Deep Learning, Data Science and Unity teams. Rapsodo is rapidly growing, and we are looking for team players who will contribute to deliver state-of-the-art solutions with us.
We're looking for a Deep Learning Engineer to join our Computer Vision & Machine Learning team!
Key Responsibilities
· Own the full deep learning model lifecycle, from data collection to deployment.
· Design and improve data collection, labeling, and annotation pipelines.
· Train, evaluate, and optimize detection, segmentation, keypoint, and tracking models.
· Develop synthetic datasets using Blender and Python-based rendering pipelines.
· Build and maintain reproducible MLOps pipelines, including experiment tracking and dataset versioning.
· Optimize models for deployment on embedded hardware.
· Define evaluation benchmarks and ensure model quality through automated testing.
· Collaborate with cross-functional teams to deliver production-ready AI solutions.
Qualifications
· Bachelor's degree in Computer Engineering, Computer Science, Mathematics, Electrical Engineering, or a related field.
· Strong Python skills with hands-on experience in PyTorch or TensorFlow.
· Good understanding of computer vision fundamentals, including camera models and image formation.
· Experience with Blender or other 3D rendering tools.
· Familiarity with Linux, Git, and Docker.
· Strong analytical and problem-solving skills with attention to data quality.
· Good communication skills in English.
· Personal projects, research, or open-source contributions are highly valued.
Nice to Have
· Experience with MLflow, Weights & Biases, DVC, ClearML, or Kubeflow.
· Experience deploying models with TensorRT, ONNX Runtime, or TensorFlow Lite.
· Knowledge of multi-object tracking or pose estimation.
· Experience with C++ for inference optimization.
· Interest in sports technologies.
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Rapsodo makes sensor-based performance measurement devices for golf, baseball, and softball, paired with data-driven software for athletes and coaches. The hardware uses doppler radar and cameras to measure metrics like ball speed, club speed, launch angle, distance, velocity, and spin rate, then streams data to mobile and web apps with video playback and shot tracing. It differentiates itself by combining multi-sport hardware with cloud and app analytics and a global presence, serving amateurs to professional teams and colleges. Its goal is to help athletes and coaches improve performance through precise data and actionable insights.
Explore more opportunities at Rapsodo