Senior AI/ML Model Evaluation Engineer (Remote)

prolificacademicltd; Stati Uniti; Remoto; USD 91.000 - 129.000; Tempo pieno

Vantaggi offerti da questo lavoro

Pay up to $80/hr

Fully remote with flexible scheduling

Quick onboarding

Descrizione del lavoro

Prolific Academic Ltd. is seeking senior AI and machine learning engineers for a paid participant opportunity in Nashville, focused on evaluating and critiquing model reasoning and code rather than shipping new systems.

The role emphasizes deep technical critique, prompt engineering, RLHF workflows, and dependencies on Transformers, CNNs, or RNNs with hands-on ML deployment experience. Fully remote-friendly, flexible scheduling, and paid assignments.

Competenze

• Degree in CS/AI/Robotics or related quantitative discipline with ML focus.
• Production experience building, deploying, or fine-tuning ML models.
• Deep expertise in transformer/CNN/RNN architectures and optimization.
• Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation workflows.

Mansioni

• Review AI-produced explanations of model architectures, loss functions, and backpropagation for technical accuracy.
• Validate ML code, including training loops, data preprocessing scripts, and evaluation notebooks.
• Provide structured human feedback to RLHF efforts to align models with user intent and safety.
• Identify and document failure modes where AI chain-of-thought reasoning collapses.
• Benchmark model outputs against taxonomies and quantitative metrics.

Conoscenze

ML focus in degree

Production ML experience

Neural network architectures

Prompt engineering / RLHF / RAG

Formazione

BS/MS/PhD in CS/AI/Robotics

Strumenti

PyTorch

TensorFlow/Keras

Python (NumPy, Pandas, SciKit-learn)

Descrizione del lavoro

Prolific Academic Ltd. is seeking senior AI and machine learning engineers for a paid participant opportunity in Nashville, focused on evaluating and critiquing model reasoning and code rather than shipping new systems.

The role emphasizes deep technical critique, prompt engineering, RLHF workflows, and dependencies on Transformers, CNNs, or RNNs with hands-on ML deployment experience. Fully remote-friendly, flexible scheduling, and paid assignments.