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

prolificacademicltd; United States; Remote; USD 83,000 - 110,000; Full time

Job summary

prolificacademic ltd is seeking experienced AI/ML engineers to join a paid expert network. Work is remote and task-based, focusing on auditing, critiquing, and improving model behavior rather than shipping production systems.

Responsibilities include reviewing explanations of architectures, auditing training loops and evaluation pipelines, and supplying high-quality feedback to align models with human intent via RL workflows. Strong emphasis on prompt engineering and model safety.

Qualifications

• BS, MS, or PhD in CS/AI/Robotics or related quantitative field focusing on ML.
• Hands-on experience building, deploying, or fine-tuning ML models in production.
• Knowledge of neural networks (Transformers/CNNs/RNNs) and optimization techniques.
• Experience with prompt engineering, RLHF, or retrieval-augmented generation workflows.
• Ability to audit complex model logic and assess training data contamination.
• Strong attention to detail to catch hallucinations and biases in outputs.

Responsibilities

• Review explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit ML code, training loops, preprocessing scripts, and evaluation pipelines for correctness.
• Provide high-quality human feedback to align models via RL workflows.
• Analyze how models reason through chain-of-thought prompts and identify logic failures.
• Run benchmarks between model outputs using technical taxonomies and metrics.

Skills

ML model development

ML deployment

Prompt engineering

RLHF

RAG evaluation

Model auditing

Education

BS in CS/AI/Robotics

MS in ML field

PhD in AI

Tools

PyTorch

TensorFlow

Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

SageMaker

Vertex AI

Weights & Biases

LangChain

Pinecone

Milvus

Weaviate

Job description

Role overview

This opportunity invites experienced AI and machine learning engineers to join a paid expert network that supports the training and evaluation of large language models. Work is task-based and remote, focused on applying deep technical judgment to audit, critique, and improve model behavior rather than shipping production systems.

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 pipelines, for correctness and efficiency
• Supply high-quality human feedback used to align models with human intent, safety, and helpfulness through reinforcement learning workflows
• Analyze how models reason through complex chain-of-thought prompts and pinpoint where logic breaks down
• Run comparative benchmarks between model outputs using technical taxonomies and quantitative performance metrics

Requirements

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

Nice to have

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

Benefits and work setup

• Remote, task-based work with flexible scheduling
• Compensation up to roughly $80 per hour for qualifying studies, with some tasks shorter than a full hour