AlephAlpha

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

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Posted within 60 days ·

  • hybrid
  • FullTime
  • Research
  • Heidelberg
  • Berlin
Work arrangement
hybrid
Employment
FullTime
Stated compensation
Not specified
Stated sponsorship
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Remote policy
hybrid
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Original job description

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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
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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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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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