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

prolificacademicltd; United States; Remote; USD 91,000 - 129,000; Part time

Benefits offered by this job

Fully remote engagement

Competitive hourly pay up to $80/hr

Short skills assessment before start

Job summary

prolificacademicltd is seeking senior AI/ML engineers for a flexible, remote contractor role in the United States. You will review explanations, audit code, and provide human feedback used to align models with human intent.

This is a contractor-style engagement with paid hourly work and a selection process through a short skills assessment. Applicants should have a strong ML background, experience with Transformers/CNNs/RNNs, and hands-on prompt engineering or RLHF.

Qualifications

• BS/MS/PhD in CS/AI/Robotics or related ML field.
• Experience deploying or fine-tuning ML models in production.
• Strong understanding of Transformer/CNN/RNN architectures.
• Hands-on with prompt engineering, RLHF, or RAG workflows.
• Audit complex model logic and identify data contamination and proofs.
• Attention to detail in spotting hallucinations and biased outputs.

Responsibilities

• Review explanations of model architectures, loss functions, and backpropagation for accuracy.
• Audit ML code and notebooks for efficiency and correctness.
• Provide high-quality human feedback for RLHF and alignment tasks.
• Analyze how models handle complex chain-of-thought prompts and identify failures.
• Benchmark model outputs using technical taxonomies and metrics.

Skills

Prompt engineering

RLHF

Model evaluation

Audit model logic

Neural networks

Python

ML deployment

Education

Bachelor's/Master's/PhD in CS/AI/Robotics or related ML field

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

AWS SageMaker

LangChain

Pinecone / Milvus / Weaviate

Job description

Role overview

This is a flexible, remote, paid opportunity for senior AI and machine learning engineers based in the Atlanta area to join an expert network that supports the training and evaluation of large language models. Participants contribute deep technical expertise through structured tasks such as reviewing model explanations, auditing ML code, and providing high-quality human feedback used to align models with human intent. It is a contractor-style engagement rather than a traditional full-time role, with paid hourly work that fits around other commitments.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit machine learning code and notebooks, including training loops, data preprocessing scripts, and model evaluations, for efficiency and correctness.
• Provide high-quality human feedback used in RLHF and alignment processes to help models behave helpfully, safely, and as intended.
• Critically analyze how an AI model navigates complex chain-of-thought prompts and pinpoint where reasoning breaks down.
• Conduct comparative benchmarking between different model outputs using specific technical taxonomies and performance metrics.

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
• Experience building, deploying, or fine-tuning ML models in a production environment.
• Professional-level understanding of neural network architectures such as Transformers, CNNs, and RNNs, and their optimization techniques.
• Hands-on 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.
• High attention to detail in spotting hallucinations, biased outputs, or 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 experience with Hugging Face Transformers.
• Familiarity with AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain.
• Familiarity with vector databases such as Pinecone, Milvus, or Weaviate for RAG evaluation.

Benefits and work setup

• Fully remote, flexible engagement with an Atlanta location specified; participants can start after passing a short skills assessment.
• Competitive hourly pay, often up to around $80 per hour depending on the study.
• Tasks typically require up to one hour of uninterrupted work, with many shorter than that.