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

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

Benefits offered by this job

Remote work

Flexible hours

Skills assessment onboarding

Job summary

Prolific Academic Ltd seeks experienced AI/ML engineers to join a remote expert network. Engage in reviewing, auditing, and refining outputs for next-generation language models, applying deep ML knowledge from home with flexible hours.

Responsibilities include auditing training loops, data preprocessing, and evaluation pipelines; providing RLHF feedback; and benchmarking outputs against technical metrics. Portland-area preference noted.

Qualifications

• Bachelor's/Master/PhD in Computer Science, AI, Robotics or related quantitative field with ML focus
• Hands-on experience building, deploying, or fine-tuning ML models in production
• Knowledge of neural network architectures (Transformers, CNNs, RNNs) and modern optimization techniques
• Experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) workflows
• Strong analytical rigor with ability to audit complex model logic and detect data contamination
• Attention to detail in identifying hallucinations, biases and logical failures in AI content

Responsibilities

• Review AI explanations of model architectures, loss functions, and backpropagation for technical accuracy
• Audit ML code and notebooks, including training loops, data preprocessing scripts, and evaluation pipelines
• Provide high-quality human feedback used in RLHF workflows to align model behavior with human intent
• Critically evaluate chain-of-thought reasoning and identify where model logic breaks down
• Conduct benchmarking of model outputs against defined technical taxonomies and metrics

Skills

ML model training

RLHF

Prompt engineering

Model evaluation

Education

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow

Hugging Face

LangChain

Weights & Biases

Vertex AI

SageMaker

Pinecone

Weaviate

Job description

Role overview

This opportunity invites experienced AI and machine learning engineers to contribute to training and evaluating next-generation large language models. Work is performed remotely as part of an expert network, where participants apply deep technical knowledge to review, audit, and refine AI outputs. The arrangement suits independent professionals based in or near Portland who want flexible, paid engagements focused on advancing model quality.

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 evaluation pipelines
• Provide high-quality human feedback used in reinforcement learning from human feedback (RLHF) workflows to align model behavior with human intent
• Critically evaluate chain-of-thought reasoning, identifying where AI model logic breaks down or produces flawed outputs
• Conduct comparative benchmarking of model outputs against defined 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
• 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 modern optimization techniques
• Practical experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) workflows
• Strong analytical rigor with the ability to audit complex model logic, detect training data contamination, and evaluate mathematical proofs
• Attention to detail in identifying hallucinations, biased outputs, and logical failures in AI-generated technical content

Nice to have

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

Benefits and work setup

• Remote participation from home with flexible hours
• Competitive hourly rates up to $80 per hour, depending on the task
• Assignments typically require up to one hour of uninterrupted work, with many shorter engagements
• Quick onboarding after passing a short skills assessment