AI Engineer/ML Engineer - Senior Developers - AI Training - Louisville, US

prolificacademicltd; USA; Remote; USD 91.000 - 129.000; Vollzeit

Benefits dieser Stelle

Hourly pay for tasks

Fully remote with flexible hours

Skills assessment gates entry

Zusammenfassung

Prolific Academic Ltd is seeking experienced AI/ML engineers to join a paid expert network that supports training and evaluation of large language models. You will review model outputs, audit code, and provide structured feedback to improve alignment and reasoning quality.

This remote, task-based role offers hourly compensation for completed tasks. The role emphasizes deep technical judgment, with several responsibilities around model explanations, code audits, and evaluation of reasoning

Qualifikationen

• BS/MS/PhD in CS, AI, Robotics or related quantitative field with ML focus.
• Hands-on experience building, deploying, or fine-tuning ML models in production.
• Knowledge of neural networks (Transformers/CNNs/RNNs) and optimization.
• Experience with RLHF or retrieval-augmented generation workflows.
• Ability to reason about ML proofs and audit model logic.
• Strong attention to detail for identifying hallucinations and biased outputs.

Aufgaben

• Review AI-generated explanations of architectures, losses, and backpropagation for technical accuracy.
• Audit ML code and notebooks, including training loops and preprocessing, for correctness.
• Provide structured human feedback to refine RLHF and improve alignment and safety.
• Evaluate how models reason through chain-of-thought prompts and identify logic breakdowns.
• Run benchmarks across outputs using defined technical criteria.
• Identify hallucinations, data contamination, and flawed mathematical reasoning in content.

Kenntnisse

Machine learning

Transformer architectures

RLHF

Prompt engineering

Model evaluation

Ausbildung

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow

HuggingFace

NumPy

Jobbeschreibung

Role overview

The position invites experienced AI and machine learning engineers to join a paid expert network that supports the training and evaluation of large language models. Contributors apply deep technical judgment to assess model outputs, audit code, and provide structured human feedback that improves model alignment and reasoning quality. It is a flexible, remote participant role based in the Louisville area rather than a traditional employment position, with hourly compensation for completed tasks.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation routines, for correctness and efficiency.
• Supply structured human feedback used to refine RLHF processes and improve model alignment, safety, and helpfulness.
• Critically evaluate how a model reasons through chain-of-thought prompts and pinpoint where the logic breaks down.
• Run comparative benchmarks across model outputs against defined technical taxonomies and performance criteria.
• Identify hallucinations, bias, training-data contamination, and flawed mathematical reasoning in AI-generated technical content.

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus.
• Hands-on experience building, deploying, or fine-tuning machine learning models in production environments.
• Professional-level knowledge of neural network architectures such as Transformers, CNNs, and RNNs, along with relevant optimization techniques.
• Practical experience with prompt engineering, reinforcement learning from human feedback (RLHF), or retrieval-augmented generation (RAG) workflows.
• Ability to reason about mathematical proofs behind ML algorithms and audit complex model logic.
• Strong attention to detail when spotting hallucinations, biased outputs, or logical failures.

Nice to have

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

Benefits and work setup

• Hourly compensation for completed tasks, with researcher budgets reaching up to $80 per hour.
• Fully remote work with flexible hours; many tasks are short, though some require roughly an hour of uninterrupted focus.
• A brief skills assessment gates entry, after which contributors can begin accepting paid assignments.