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

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

Benefits offered by this job

Fully remote

Up to $80/hour

Job summary

prolificacademicltd is seeking a senior contract AI/ML engineer to shape the next generation of large language models. You will work remotely on focused sessions up to one hour, contributing your production ML background on technically demanding tasks.

After a brief 10-15 minute skills assessment, researchers typically earn up to $80 per hour for specialist contributions. Candidates should have advanced degrees in CS/AI and hands-on experience with transformers, RLHF workflows, and ML auditing.

Qualifications

• BS, MS, or PhD in CS/AI/related quantitative field focused on ML.
• Production experience building, deploying, or fine-tuning ML models.
• Strong command of neural network architectures (Transformers, CNNs, RNNs) and optimization methods.
• Hands-on experience with prompt engineering, RAG pipelines, or RLHF workflows.
• Capacity to audit complex model logic, detect training-data contamination, and assess mathematical proofs behind ML algorithms.
• Meticulous attention to detail in catching hallucinations, biased outputs, or logical failures.

Responsibilities

• Evaluate AI-generated explanations of model architectures, loss functions, and backpropagation for technical soundness.
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation logic.
• Provide the structured human feedback that powers RLHF alignment with intent, safety, and helpfulness.
• Diagnose where AI reasoning breaks down on complex chain-of-thought prompts.
• Benchmark competing model outputs against predefined technical taxonomies and metrics.

Skills

ML background

Prompt engineering

RLHF workflows

Model auditing

Attention to detail

Hardware-agnostic ML

Education

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

Tools

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, Scikit-learn)

Hugging Face Transformers

AWS SageMaker

Vector databases (Pinecone/Milvus/Weaviate)

Job description

Role overview

A senior contract role for seasoned AI and machine learning engineers who want to shape the next generation of large language models. Contributors complete paid, technically demanding tasks using their production ML background, working remotely on focused sessions up to one hour at a time. Entry requires passing a brief 10-15 minute skills assessment, after which researchers typically pay up to $80 per hour for specialist contributions.

Responsibilities

• Evaluate AI-generated explanations of model architectures, loss functions, and backpropagation for technical soundness
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation logic
• Provide the structured human feedback that powers RLHF alignment with intent, safety, and helpfulness
• Diagnose where AI reasoning breaks down on complex chain-of-thought prompts
• Benchmark competing model outputs against predefined technical taxonomies and metrics

Requirements

• BS, MS, or PhD in Computer Science, AI, Robotics, or a related quantitative field focused on ML
• Production experience building, deploying, or fine-tuning ML models
• Strong command of neural network architectures (Transformers, CNNs, RNNs) and optimization methods
• Hands‑on work with prompt engineering, RAG pipelines, or RLHF workflows
• Capacity to audit complex model logic, detect training‑data contamination, and assess mathematical proofs behind ML algorithms
• Meticulous attention to detail in catching hallucinations, biased outputs, or logical failures

Nice to have

• Expert-level proficiency in PyTorch or TensorFlow/Keras
• Advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers
• Familiarity with AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain
• Comfort with vector databases such as Pinecone, Milvus, or Weaviate

Benefits and work setup

• Fully remote, flexible scheduling with no minimum hours
• Quick 15-minute onboarding once the assessment is passed
• Compensation up to $80 per hour, with task pay and duration disclosed up front
• Location: Tucson, United States