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Open nowPosted 62 days ago

Deep Learning Engineer

Workable (global search)108,016 open roles

Where
Ankara, Turkey
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Your applicationOpen nowDeep Learning EngineerWorkable (global search) · Ankara, Turkey

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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 62 days ago

Workable (global search) median: 7 days open

The posting

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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