AI Engineer/ML Engineer - Senior Developers - AI Training - Las Vegas, US

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

Benefits offered by this job

Remote work

Flexible hours

Short onboarding

Job summary

prolificacademicltd is recruiting senior AI and ML Engineers to support training and evaluation of advanced large language models. You will work remotely on short, task-based studies with flexible hours, earning per task compensation up to $80/hour.

Responsibilities include auditing ML code and notebooks, validating model explanations, and providing high-quality feedback to RLHF pipelines to improve model alignment.

Qualifications

• PhD/MS/BS in CS/AI/related quantitative field with ML focus.
• Production-level experience building, deploying, or fine-tuning ML models.
• Strong command of Transformer, CNNs, RNNs architectures and their optimization.
• Hands-on prompt engineering, RLHF, or retrieval-augmented generation workflows.

Responsibilities

• Evaluate AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness.
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation harnesses, for quality and efficiency.
• Contribute high-quality human feedback that informs RLHF pipelines and strengthens model alignment.
• Diagnose how a model handles chain-of-thought prompts and flag where its reasoning fails.
• Run structured benchmarks across model outputs based on technical taxonomies and metrics.

Skills

ML research

Prompt engineering

RLHF

Model evaluation

Attention to detail

Education

BS/MS/PhD in CS/AI/related quantitative field

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

NumPy

Pandas

Scikit-learn

Job description

Role overview

An expert contributor network is hiring senior AI and Machine Learning Engineers to support the training and evaluation of cutting-edge large language models. Engineers are paid per task to apply their production experience to structured research assignments, with most studies designed for short, focused sessions. The position is fully remote and built around flexible participation that fits around existing commitments.

Responsibilities

• Evaluate AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation harnesses, for quality and efficiency
• Contribute high-quality human feedback that informs RLHF pipelines and strengthens model alignment
• Diagnose how a model handles chain-of-thought prompts and flag exactly where its reasoning fails
• Run structured comparative benchmarks across model outputs based on 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
• Production-level experience building, deploying, or fine-tuning machine learning models
• Strong command 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
• Capacity to audit complex model logic, detect training data contamination, and scrutinize mathematical underpinnings of ML algorithms
• Keen attention to detail for surfacing hallucinations, biased outputs, and logical inconsistencies in AI-generated content

Nice to have

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

Benefits and work setup

• Competitive hourly rates, with researcher-driven tasks often paying up to $80 per hour
• Remote work from home with completely flexible hours
• Streamlined onboarding following a 10-15 minute skills assessment; tasks are scoped to allow roughly one hour of uninterrupted focus