Machine Learning Research Assistant (Student Role or Minijob)
Machine Learning Research Assistant (Student Role or Minijob)
Machine Learning Research Assistant (Student Role or Minijob)
Machine Learning Research Assistant (Student Role or Minijob)
experial
Informationsdienste
Wuppertal
- Verifizierte Job-Anzeige
- Art der Anstellung: Studierende
- Remote
- Zu den Ersten gehören
Machine Learning Research Assistant (Student Role or Minijob)
Über diesen Job
Intro
At experial, we are building the future of customer insights: fast, intelligent, and always available. By creating digital twins of real customers, we enable companies to instantly gather feedback on any question - without waiting days or weeks for interviews or surveys. Our clients include some of Germany’s largest B2C brands in finance and retail. Backed by top-tier VCs and AI experts, we are moving fast - and we want you to grow with us.
We are currently looking for student research assistants (flexible Minijob or HiWi) to support our machine learning team in experimentation and development in the areas of multi-agent ML/AI evaluation, MLOps, and optimization - with a strong focus on language and multi-modal models.
Tasks
Your Role
You will work closely with our ML team and co-founders on hands-on research, prototyping, and development in one or more of the following areas:
- Developing, testing, and improving evaluation methods for multi-agent systems
- Running research experiments, analyzing failure cases, and testing improvements for ML and agentic components
- Investigating model weaknesses, capabilities, attack modes, and robustness
- Translating ML components into production-ready product features
Work Mode
- Fully remote
- Option 1: 5–10 hours/week as a remote mini-job (tax-free) - ideal for gaining relevant industry experience alongside a university role, especially to complement academic work with real-world lab and product exposure
- Option 2: 15–20 hours/week as a HiWi / working student - schedule adapted to your university and job commitments
- adjusted to your university and job schedules
- co-supervision of a master thesis if the subject aligns with the work - get payed for your MSc thesis
Requirements
Minimum Requirements
- python skills (especially OOP, LLMs)
- Experience training or evaluating deep learning models — PyTorch
- Familiarity with transformer-based architectures in NLP or CV
- Comfort with CLI, git, SSH, and command line workflows
- Ability to communicate results clearly in English (spoken and written) — German is a plus for analysis
- A current BSc, MSc, PhD student enrolment at a German university or FH
Bonus Points
- 2+ years of experience in ML-based (uni) projects/ implementations
- Skills in pandas, plotly, numpy, agentic frameworks
- Experience with pretraining or fine-tuning or RL for LLM/ SLM/ VLM
- Experience with shared GPU environments (e.g., via slurm, AWS, serverless)
- Familiarity with evaluation tracking tools like MLFlow/ WandB
Benefits
What we offer
- fully remote work
- Supportive and efficient environment with startup energy
- Teaching highly relevant AI/ ML skills for CV building to prepare for the job market
- Depending on performance possibility to join the team after finished degree
- Mentorship from experienced AI engineers and product leads
- Compensation:
- as Main job: As HiWi/ working student: €15/h–€20/h depending on experience for up to 20h/week or
- as side job: Tax free side job for experience/ CV: Minijob €556/month for 5-10h/ week — depending on experience and time (approx. €14/h - €28/h)
- Early co-authorship opportunities if we publish research together
- Access to GPU infrastructure
Closing
What are the next steps:
If you are passionate about engineering, and ready to co-create impactful AI solutions, then don't hesitate to reach out! We are looking for a good fit, not a perfect fit.
Apply now with
- a clean CV (focus/ highlight on relevant skills and ML experience) — you can include courses, projects and links
- a short letter of motivation (simple .txt is fine) — AI generated is ok (but we will ask about the details later), speech recorded is ok, spelling isn't relevant, formatting isn't relevant.
But please include a short description of:
- Why this fits your experience/ skills — fit to us
- What you'd like to learn from and with us — fit to your plans
- Any relevant projects (with code links, if possible) — examples go a long way
Join our team and learn how to carry AI and ML from idea to implementation to product.