AI Engineer/ML Engineer - Senior Developers - AI Training - Germany

Prolific; Germany (OH); Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Flexible hours

Remote work

Job summary

Prolific is seeking an AI & Machine Learning Engineer – AI Training to lead training and evaluation of large language models. You will audit training pipelines, improve RLHF processes, and ensure model outputs meet high standards of accuracy and safety.

The role requires deep learning mastery, experience with transformers, and hands-on work with LLM workflows across production environments. Remote-friendly, global team, with competitive compensation.

Qualifications

• Education in a quantitative field with ML focus.
• Experience building, deploying, or fine-tuning ML models in production.
• Deep learning mastery across Transformers, CNNs, RNNs.
• Hands-on LLM work with Prompting, RLHF, or RAG.
• Ability to audit model logic, data contamination, and math proofs.
• Strong analytical critique of AI outputs and reasoning.

Responsibilities

• Evaluate LLM architecture logic for technical accuracy.
• Audit ML code and notebooks for efficiency and correctness.
• Refine RLHF frameworks with high-quality human feedback.
• Analyze model reasoning and identify failures in chain-of-thought prompts.
• Benchmark model outputs using technical taxonomies and metrics.

Skills

ML model training & deployment

Prompt Engineering

RLHF

RAG workflows

AI safety evaluation

Model auditing

Education

BS/MS/PhD in Computer Science/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, Scikit-learn)

Hugging Face Transformers

AWS SageMaker

Google Vertex AI

Weights & Biases

LangChain

Pinecone/Milvus/Weaviate

Job description

AI & Machine Learning Engineer – AI Training

This role focuses on training and evaluating large language models, leveraging deep machine learning expertise.

What You’ll Bring

• Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
• Professional Experience: experience building, deploying, or fine‑tuning ML models in a production environment.
• Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
• LLM Specialization: hands‑on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval‑Augmented Generation) workflows.
• Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
• Analytical Critique: high attention to detail in spotting hallucinations, biased outputs, or logical failures in AI-generated technical content.

What You’ll Be Doing in the Role

• Evaluate LLM Architecture Logic: review AI‑generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit Code & Notebooks: validate ML‑specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
• Refine RLHF Frameworks: provide high‑quality human feedback necessary to align models with human intent, safety, and helpfulness.
• Analyze Model Reasoning: critically assess how an AI model navigates complex chain‑of‑thought prompts and identify where the reasoning breaks down.
• Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.

Key Technologies

• Frameworks: expert proficiency in PyTorch or TensorFlow/Keras.
• Language & Data: advanced Python (NumPy, Pandas, Scikit‑learn) and experience with Hugging Face Transformers.
• Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
• Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.

Benefits

Competitive pay rates, flexible hours, and the ability to work from home.

We provide a platform that connects researchers and companies with a global pool of participants, enabling the collection of high‑quality, ethically sourced human behavioural data and feedback.

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