AI Engineer/ML Engineer - Senior Developers - AI Training - Belfast, UK

prolificacademicltd; United States; Remote; USD 66,000 - 110,000; Part time

Benefits offered by this job

Hourly pay

Job summary

This is a participant-based, paid contract role based in Belfast with a flexible remote schedule. You will contribute to training and evaluation of large language models, reviewing explanations, auditing code, and providing structured human feedback to RLHF workflows.

Candidates should have a strong ML background with hands-on experience in neural networks, transformers, and ML tooling. Hourly compensation up to $80, with a short skills assessment and quick onboarding once accepted.

Qualifications

• BS/MS/PhD in CS/AI with ML focus.
• Hands-on experience deploying or fine-tuning ML models.
• Knowledge of Transformers/CNNs/RNNs.
• Experience with prompt engineering or RLHF workflows.
• Ability to audit training data and ML proofs.

Responsibilities

• Review explanations of model architectures for correctness.
• Audit ML code, training loops, preprocessing scripts for efficiency.
• Provide structured feedback for RLHF workflows.
• Assess model reasoning on chain-of-thought prompts.
• Benchmark outputs against defined metrics and taxonomies.

Skills

ML model training

Transformer architectures

Prompt engineering

RLHF workflows

Model evaluation

Code auditing

Education

BS in CS

MS/PhD ML

Tools

PyTorch

TensorFlow/Keras

HuggingFace Transformers

AWS SageMaker

Job description

Role overview

Join an expert network of machine learning professionals contributing to the training and evaluation of large language models. This is a participant-based, paid contract role based in Belfast where your technical expertise directly shapes AI model accuracy, safety, and reasoning quality. Successful candidates complete paid study tasks, typically requiring up to one hour of focused work, on a flexible remote schedule.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness
• Audit machine learning code, training loops, preprocessing scripts, and evaluation notebooks for efficiency and accuracy
• Provide structured human feedback that supports reinforcement learning from human feedback (RLHF) workflows and model alignment
• Critically assess how models navigate complex chain-of-thought prompts and pinpoint where reasoning breaks down
• Benchmark and compare model outputs against defined technical taxonomies and performance metrics

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus
• Hands-on production experience building, deploying, or fine-tuning ML models
• Professional-level understanding of neural network architectures such as Transformers, CNNs, and RNNs, plus optimization techniques
• Practical experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) workflows
• Ability to audit model logic, flag potential training-data contamination, and evaluate the mathematical proofs behind ML algorithms
• Strong attention to detail for spotting hallucinations, biased outputs, or logical failures in AI-generated technical content

Nice to have

• Proficiency with PyTorch or TensorFlow/Keras
• Advanced Python skills including NumPy, Pandas, Scikit-learn, and Hugging Face Transformers
• Experience with cloud MLOps platforms such as AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain
• Familiarity with vector databases like Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup

• Hourly compensation commonly up to $80, depending on study requirements
• Fully remote with flexible scheduling aligned to available studies
• Short 10–15 minute skills assessment as the entry point, with quick onboarding once accepted