AI Engineer/ML Engineer - Senior Developers - AI Training - San Diego, USA

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

Benefits dieser Stelle

Hourly pay up to $80

Fully remote with flexible hours

Brief onboarding

Zusammenfassung

prolificacademicltd is seeking experienced AI/ML engineers for a remote, flexible contributor-track role focused on training and evaluating large language models. You will review explanations, audit training code, and provide high-quality feedback used in RLHF to align models with human intent.

Ideal candidates have advanced degrees in CS/AI, hands-on experience with Transformer-based models, and proficiency in PyTorch or TensorFlow.

Qualifikationen

• Bachelor’s, Master’s or PhD in CS/AI/related quantitative field with ML emphasis.
• Professional experience building, deploying, or fine-tuning ML models in production.
• Deep familiarity with Transformer, CNN, RNN architectures and optimizations.
• Hands-on prompt engineering, RLHF pipelines, or retrieval-augmented generation (RAG).
• Sharp attention to detail to catch hallucinations, biases, or logical AI failures.

Aufgaben

• Review AI-generated explanations of model architectures, losses, and backpropagation for accuracy.
• Audit ML code and notebooks: training loops, preprocessing scripts, and evaluation routines.
• Provide high-quality human feedback used in RLHF to align models with human intent and safety.
• Analyze model behavior on chain-of-thought prompts and flag breakdowns in reasoning.
• Conduct comparative testing across model outputs using defined technical criteria.

Kenntnisse

ML research

prompt engineering

code auditing

RLHF evaluation

attention to detail

Ausbildung

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

Tools

PyTorch

TensorFlow/Keras

AWS SageMaker

LangChain

Pinecone/Milvus/Weaviate

Jobbeschreibung

Role overview

This participant-track opportunity invites experienced AI and machine learning engineers to help train and evaluate large language models through structured paid research tasks. Instead of a conventional employment arrangement, contributors work remotely on a flexible basis, lending their professional judgment to sharpen model behavior. The position is well suited to senior engineers in the San Diego area who can commit to focused blocks of technical review.

Responsibilities

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Audit machine learning code and notebooks, covering training loops, data preprocessing scripts, and evaluation routines.
• Supply high-quality human feedback used in reinforcement learning from human feedback (RLHF) to align models with human intent and safety.
• Analyze how models navigate complex chain-of-thought prompts and flag breakdowns in their reasoning.
• Conduct comparative testing across model outputs using defined technical taxonomies and performance criteria.

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning emphasis.
• Professional experience building, deploying, or fine-tuning ML models in a production environment.
• Deep familiarity with neural network architectures such as Transformers, CNNs, and RNNs, including optimization techniques.
• Hands-on work with prompt engineering, RLHF pipelines, or retrieval-augmented generation (RAG) systems.
• Sharp attention to detail for catching hallucinations, biased outputs, or logical failures in AI-generated technical content.
• Capability to audit complex model logic, evaluate mathematical proofs behind ML algorithms, and detect potential training data contamination.

Nice to have

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

Benefits and work setup

• Hourly compensation up to $80 for qualifying contributors.
• Fully remote work with flexible hours and the option to work from home.
• Brief onboarding through a 10 to 15 minute skills assessment.
• Tasks typically require one hour of uninterrupted focus, though many are shorter.