AI Engineer/ML Engineer - Senior Developers - AI Training - Long Beach, US

prolificacademicltd; USA; Remote; USD 91.000 - 129.000; Vollzeit

Benefits dieser Stelle

Remote work

Flexible hours

Up to $80/hour

Zusammenfassung

prolificacademicltd is seeking experienced AI/ML engineers to join a paid expert network that supports training and evaluation of large language models. You will audit outputs, review model reasoning, and provide structured feedback to improve alignment and safety.

This remote, task-based role offers hourly compensation for completed work. Candidates should have advanced degrees in CS/AI or related fields and hands-on production ML experience.

Qualifikationen

• BS, MS or 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 related optimization techniques.
• Experience with prompt engineering, RLHF or RAG workflows.
• Ability to reason about ML math proofs and audit complex model logic.
• Strong attention to detail in spotting hallucinations, bias or faulty reasoning.

Aufgaben

• Review explanations of model architectures, losses and backpropagation for technical accuracy.
• Audit ML code and notebooks for correctness and efficiency.
• Supply structured human feedback to refine RLHF and model alignment.
• Evaluate how a model reasons through chain-of-thought prompts and identify logic breakdowns.
• Run benchmarks comparing model outputs against defined technical taxonomies and performance criteria.
• Identify hallucinations, bias, data contamination, and flawed mathematical reasoning in AI content.

Kenntnisse

ML model production

Neural network architectures

Prompt engineering RLHF RAG

Proof-based reasoning

Detail-oriented auditing

Ausbildung

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow/Keras

NumPy

Pandas

Hugging Face Transformers

LangChain

Weights & Biases

Pinecone

Jobbeschreibung

Role overview

The position invites experienced AI and machine learning engineers to join a paid expert network that supports the training and evaluation of large language models. Contributors apply deep technical judgment to assess model outputs, audit code, and provide structured human feedback that improves model alignment and reasoning quality. It is a flexible, remote participant role based in the Long Beach area rather than a traditional employment position, with hourly compensation for completed tasks.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation routines, for correctness and efficiency.
• Supply structured human feedback used to refine RLHF processes and improve model alignment, safety, and helpfulness.
• Critically evaluate how a model reasons through chain-of-thought prompts and pinpoint where the logic breaks down.
• Run comparative benchmarks across model outputs against defined technical taxonomies and performance criteria.
• Identify hallucinations, bias, training-data contamination, and flawed mathematical reasoning in AI-generated technical content.

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 machine learning models in production environments.
• Professional-level knowledge of neural network architectures such as Transformers, CNNs, and RNNs, along with relevant optimization techniques.
• Practical experience with prompt engineering, reinforcement learning from human feedback (RLHF), or retrieval-augmented generation (RAG) workflows.
• Ability to reason about mathematical proofs behind ML algorithms and audit complex model logic.
• Strong attention to detail when spotting hallucinations, biased outputs, or logical failures.

Nice to have

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

Benefits and work setup

• Hourly compensation for completed tasks, with researcher budgets reaching up to $80 per hour.
• Fully remote work with flexible hours; many tasks are short, though some require roughly an hour of uninterrupted focus.
• A brief skills assessment gates entry, after which contributors can begin accepting paid assignments.