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

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

Benefits dieser Stelle

Hourly pay up to $80

Fully remote work

Flexible scheduling

Fast onboarding

Zusammenfassung

prolificacademicltd seeks senior AI/ML engineers for discrete, paid studies to train and evaluate large language models. Work is hourly, fully remote, and requires deep ML expertise for high-quality feedback in alignment pipelines.

Responsibilities include auditing explanations, reviewing training code, providing RLHF-based ratings, and benchmarking model outputs. Studies vary in length and complexity.

Qualifikationen

• BS, MS or PhD in Computer Science, AI, Robotics or related quantitative field with ML focus.
• Professional experience building, deploying, or fine-tuning ML models in production.
• Strong grasp of neural nets including Transformers, CNNs, RNNs and their optimization.
• Hands-on with prompt engineering, RLHF, or retrieval-augmented generation (RAG).
• Able to audit complex model logic and detect data contamination and ML math foundations.
• Sharp analytical eye for hallucinations, biased outputs, and logical failures.

Aufgaben

• Audit AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy.
• Review ML code and notebooks, including training loops, data preprocessing scripts, and evaluation routines.
• Contribute high-quality human ratings used in RLHF workflows to steer models toward safer outputs.
• Trace how a model navigates chain-of-thought prompts and identify reasoning breakdowns.
• Run benchmarks comparing model outputs against defined taxonomies and metrics.

Kenntnisse

ML model deployment

Transformer/RNN/CNN knowledge

Prompt engineering

RLHF/RAG familiarity

Model auditing & debugging

Ausbildung

BS/MS/PhD in CS/AI/Robotics or related quant.

Tools

PyTorch

TensorFlow/Keras

Hugging Face Transformers

AWS SageMaker / Vertex AI

Weights & Biases / LangChain

Vector databases (Pinecone/Milvus/Weaviate)

Jobbeschreibung

Role overview

This is a paid participant opportunity for senior AI and machine learning engineers to help train and evaluate large language models through structured, task-based work. Rather than a traditional full-time role, contributors take on individual studies that pay by the hour and draw on deep technical expertise to shape model behavior. The mission centers on supplying the high-quality human feedback that modern alignment pipelines depend on.

Responsibilities

• Audit AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy
• Review ML code and notebooks, including training loops, data preprocessing scripts, and evaluation routines, flagging inefficiencies or bugs
• Contribute high-quality human ratings used in reinforcement learning from human feedback (RLHF) workflows to steer models toward safer, more helpful outputs
• Trace how a model navigates chain-of-thought prompts and pinpoint where its reasoning breaks down
• Run comparative benchmarks of competing model outputs against defined taxonomies and performance metrics

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus
• Professional experience building, deploying, or fine-tuning ML models in production settings
• Strong grasp of neural network architectures including Transformers, CNNs, and RNNs, along with their optimization techniques
• Hands-on work with prompt engineering, RLHF, or retrieval-augmented generation (RAG) systems
• Ability to audit complex model logic, detect training data contamination, and assess the mathematical underpinnings of ML algorithms
• Sharp analytical eye for hallucinations, biased outputs, and logical failures in AI-generated technical content

Nice to have

• Expert proficiency in PyTorch or TensorFlow and Keras
• Advanced Python skills with NumPy, Pandas, and Scikit-learn, plus experience using Hugging Face Transformers
• Familiarity with cloud ML platforms such as AWS SageMaker or Google Vertex AI, and tooling like Weights and Biases or LangChain
• Experience with vector databases such as Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup

• Hourly compensation that can reach up to $80 depending on the study
• Fully remote work with flexible scheduling
• Short 10 to 15 minute skills assessment followed by fast onboarding
• Most tasks fit within roughly one hour of focused, uninterrupted work, with many shorter in length