Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- Senior Machine Learning Engineer for Disney designing production ML systems impacting revenue and viewer experience. Collaborate across teams in low-latency, high-throughput environments.
Responsibilities
- Apply modern machine learning techniques to advertising use cases such as inventory forecasting, pricing, targeting, and efficient ad delivery
- Design, implement, and iterate on ML solutions from experimentation through production deployment and ongoing optimization
- Build and scale ML architectures that balance model quality, latency, throughput, reliability, and cost
- Design and maintain feature pipelines and feature stores supporting both real-time inference and offline training
- Own major components of the model lifecycle, including experimentation, validation, deployment, monitoring, and iteration
- Analyze experimental results and partner with product and engineering stakeholders to support data-informed decisions
- Ensure models are observable, debuggable, and explainable in production environments
- Implement monitoring for model performance, drift, bias, and overall system health
- Contribute to engineering excellence through high-quality code, sound system design, and operational best practices
- Provide technical guidance through code reviews, design discussions, and knowledge sharing
Requirements
- Bachelor's degree in Computer science or related field of study
- 5+ years of software engineering experience
- Minimum 3 years of hands-on experience developing and deploying machine learning systems in production
- Strong knowledge of machine learning fundamentals, mathematics, and statistics
- Experience operating ML systems in low-latency, high-throughput environments
- Strong communication and collaboration skills with both technical and non-technical partners
- Solid foundations in algorithms, data structures, and numerical optimization
- Proficiency in Python (primary), with experience in Java and SQL
- Experience with modern ML frameworks and tooling such as TensorFlow, PyTorch, and Hugging Face
- Experience with one or more of the following: Deep learning methodologies, Transformer architectures, Multimodal embedding techniques, Large language models, Retrieval-augmented generation architectures
- Experience building systems on cloud-native infrastructure and distributed platforms.
- Proven ability to thrive in a fast-paced, data-driven, and collaborative environment.
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
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