Machine Learning Engineer

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Machine Learning Engineer in Others

Sportradar
Full time
Email

Others
10/07/2026
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Ljubljana, Slovenia

Responsibilities

Analyze, explore, and visualize large-scale sports, betting, tracking, and behavioral datasets using statistical and data science methods.
Develop predictive, statistical, deep learning, and generative AI models.
Design and implement production-grade data processing, training, validation, and inference pipelines.
Validate models and hypotheses through back-testing, simulations, experimentation, and algorithm evaluation.
Deploy AI solutions on Sportradar’s AI platform and support model monitoring, maintenance, and continuous improvement.
Design analytical approaches that enhance sports, betting, tracking, and product services.
Collaborate with product owners, technical leads, and software engineers to integrate model outputs into products.
Present complex technical findings to technical and non-technical stakeholders.

Requirements

Strong knowledge of machine learning, statistics, and data science.
Proven software engineering experience and strong programming skills in Python and Java.
Experience building and deploying production-grade machine learning solutions.
Proficiency with modern machine learning frameworks such as PyTorch and large-scale data processing.
Advanced SQL skills and experience working with large datasets.
Experience in predictive modeling, risk management, trading, quantitative analytics, deep learning, natural language processing, transformers, sequence modeling, or representation learning.
Experience validating models through experimentation, simulations, and back-testing.
Experience with cloud computing, preferably AWS.
Experience with agentic coding tools such as Cursor or Claude Code.
A bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
Fluent written and spoken English.
Kafka, Flink, real-time analytics, distributed systems, tracking, time-series, computer vision, pose estimation, or spatiotemporal data experience is a bonus.

Benefits

Collaborative global environment with social events, team-building, and employee communities including Women in Tech and Pride groups.
Global Employee Assistance Programme.
Access to Calm and Reulay well-being apps.
Online training videos.
Flexible working hours and autonomy in managing work.
Fully on-site work five days per week, with certain location-dependent exemptions.
Structured recruitment process including screening, technical interview, and onsite interview.

Sportradar

Sportradar delivers real‑time data, analytics, and integrity solutions that empower sports organizations to enhance fan engagement, streamline operations, and safeguard the integrity of competitions. By combining cutting‑edge technology with deep industry expertise, we help teams, leagues, and br...

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