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
- Associate Machine Learning Engineer contributing to impactful ML projects at Tubi. Participants rotate through engineering teams, gaining hands-on experience in a fast-paced tech environment.
Responsibilities
- Rotate across three machine learning engineering teams, gaining exposure to different technical disciplines
- Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
- Ship production ML systems and features that impact millions of real users
- Leverage cutting-edge AI technologies to build technical solutions at scale
- Define success metrics and evaluate impact via offline and online experiments
- Monitor, evaluate, and optimize the performance of deployed models
- Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement
- Participate in mentorship, technical training, and networking events throughout the program
- Engage in engineering-wide initiatives to improve processes and technical standards
Requirements
- Master’s or PhD degree in Computer Science or a related field with emphasis on Machine Learning
- Strong coding proficiency in at least one programming language (e.g., Python, Java, C++, Go)
- Solid understanding of computer science fundamentals, algorithms, and system design
- Demonstrated understanding and interest in machine learning engineering
- Passion for problem-solving, collaboration, and building scalable systems
- Strong communication skills and ability to work in a team-oriented environment
- Up to three years of combined professional experience, including internships (preferred)
- Familiarity with cloud platforms (AWS, GCP, Azure) and DevOps tools (preferred)
Benefits
- Medical/dental/vision insurance
- 401(k) plan
- Paid time off
- Flexible Time off Policy
- Generous Parental Leave Program
- Monthly wellness reimbursement
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