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Senior AI Researcher: LLM post-training for hallucination reduction (f/m/d)

at Alephalpha

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May require office time No longer listed on its source board ● Posted 2 days ago Heidelberg Data

About this role

Who we are

Aleph Alpha’s mission is to deliver sovereign, human-centric AI to governmental institutions and large enterprises. To that end, we deliver category-defining AI innovation that enables open, accessible, and trustworthy deployment of GenAI in industrial applications. Our organization develops foundational models and next-generation methods that make it easy and affordable for Aleph Alpha’s customers to increase productivity in development, engineering, logistics, and manufacturing processes.

About the role

We are looking for a (Senior) AI Researcher to join our hallucination reduction capability team to push the boundaries in LLM post-training (SFT and RL).

We're one of the few places in Europe training foundation models from scratch. You will be part of a team of (senior) researchers and PhD interns doing cutting-edge research across pre-, mid- and post-training, grounding and specialized models with hundreds of GPUs at our disposal.

What will you do
  • Core Research & Development: Design, execute, and scale post-training methodologies (SFT, RL) specifically aimed at eliminating model hallucinations and making them grounded in evidence.

  • Uncertainty & Reliability: Research and implement techniques in uncertainty estimation, calibration, self-consistency, and self-correction mechanisms to enable models to identify and signal when they “don't know”.

  • Post-Training Pipelines: Build and optimize high-throughput, distributed fine-tuning and training pipelines across multi-node GPU clusters.

  • Evaluation & Benchmarking: Design and implement rigorous evaluation methods to benchmark hallucination rates, truthfulness, and reasoning accuracy.

  • Technical Ownership: Drive research projects independently from initial hypothesis to scalable production implementation and technical reports.

Qualifications
  • Hands-on experience fine-tuning or post-training LLMs using modern distributed training frameworks.

  • Track record of research or implementation in at least one of the following domains:

    • Hallucination mitigation / truthfulness alignment / grounding in RAG

    • Uncertainty estimation, or out-of-distribution detection

    • Retrieval-Augmented Generation evaluation / alignment, refusal behavior calibration, or claim verification

  • Strong programming skills (Python & PyTorch).

Compensation and Benefits
  • Become part of an AI revolution!

  • 30 days of paid vacation

  • Access to a variety of fitness & wellness offerings via Wellhub

  • Mental health support through nilo.health

  • Substantially subsidized company pension plan for your future security

  • Subsidized Germany-wide transportation ticket

  • Budget for additional technical equipment

  • Flexible working hours for better work-life balance and hybrid working model

  • JobRad® Bike Lease

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Real Remote Score 44/100 · see the full breakdown

Real Remote Score

44/100

Mixed

Comp
0/25
Location
4/25
Source
5/15
Clarity
15/15
Freshness
20/20
Why this score? ▾
  • Compensation · No salary disclosed 0/25
  • Location · Specific city or narrow scope 4/25
  • Source · Generic aggregator 5/15
  • Role clarity · Seniority + stack/role both clear 15/15
  • Freshness · Posted 2 days ago: within last week 20/20

How the Real Remote Score is calculated → · Score appeals & corrections

Hybrid Transparency Score 15/100 · see the full breakdown

Hybrid Transparency Score

15/100

Weak

Days
0/30
Location
15/30
Schedule
0/15
Relocation
0/15
Source
0/10

This role is hybrid: it expects some in-office presence. HTS grades how clearly the employer discloses the hybrid terms. How the Hybrid Transparency Score works →

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