Remote AI Training & Evaluation Engineer (Contract)

prolificacademicltd; Stati Uniti; Remoto; USD 91.000 - 129.000; Part-time

Descrizione del lavoro

prolificacademicltd is offering a paid contract role in Austin with fully remote scheduling. You will review explanations of model architectures, audit training code, and provide feedback to RLHF workflows to improve model alignment and safety.

The position requires hands-on ML development experience and deep knowledge of Transformers, CNNs, and RNNs, with emphasis on debugging, data integrity, and bias spotting in AI outputs.

Competenze

• BS, MS, or PhD in CS/AI/Robotics or related quantitative field with ML focus.
• Hands-on production experience building, deploying, or fine-tuning ML models.
• Knowledge of Transformer, CNNs, and RNN architectures and optimization.
• Experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG).
• Ability to audit model logic and assess data contamination and proofs behind ML algorithms.
• Strong attention to detail to spot hallucinations or biased outputs in AI content.

Mansioni

• Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical correctness.
• Audit ML code, training loops, preprocessing scripts, and evaluation notebooks for efficiency and accuracy.
• Provide structured human feedback that supports RLHF workflows and model alignment.
• Critically assess how models navigate complex chain-of-thought prompts and pinpoint where reasoning breaks down.
• Benchmark and compare model outputs against defined technical taxonomies and performance metrics.

Conoscenze

ML model development

Neural networks

Prompt engineering

RLHF

Model evaluation

Code auditing

Formazione

BS/MS/PhD in CS/AI/Robotics or related quantitative field

Strumenti

PyTorch

TensorFlow/Keras

NumPy/Pandas

Scikit-learn

Hugging Face Transformers

Descrizione del lavoro

prolificacademicltd is offering a paid contract role in Austin with fully remote scheduling. You will review explanations of model architectures, audit training code, and provide feedback to RLHF workflows to improve model alignment and safety.

The position requires hands-on ML development experience and deep knowledge of Transformers, CNNs, and RNNs, with emphasis on debugging, data integrity, and bias spotting in AI outputs.