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

prolificacademicltd; USA; Remote; USD 66.000 - 110.000; Vollzeit

Benefits dieser Stelle

Competitive hourly rates

Remote work from home

Flexible hours

Skills assessment

Zusammenfassung

Prolific Academic Ltd. is hiring senior AI/ML engineers to support training and evaluation of large language models. Roles are paid per task, fully remote with flexible participation designed around existing commitments.

You will evaluate explanations, audit code, and provide feedback for RLHF pipelines, ensuring high-quality model alignment. Candidates should have strong ML foundations and experience with transformers.

Qualifikationen

• BS/MS/PhD in CS/AI/ML or related quantitative field.
• Production-level ML experience and deployment/fine-tuning.
• Experience with neural network architectures and optimization techniques.
• Hands-on prompt engineering, RLHF, or retrieval-augmented generation workflows.
• Ability to audit complex model logic and detect data contamination.
• Attention to surfacing hallucinations and biased outputs in AI content.

Aufgaben

• Evaluate AI-generated explanations of architectures, loss functions, and backpropagation.
• Audit ML code/notebooks for quality and efficiency.
• Contribute high-quality human feedback for RLHF pipelines.
• Diagnose model handling of chain-of-thought prompts and locate reasoning failures.
• Run structured benchmarks across model outputs using technical metrics.

Kenntnisse

Transformers

RLHF

Prompt engineering

Model evaluation

Python

PyTorch

Ausbildung

BS/MS/PhD in CS/AI/ML

Tools

PyTorch

TensorFlow

Hugging Face

Jobbeschreibung

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