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

prolificacademicltd; United States; Remote; USD 91,000 - 129,000; Full time

Benefits offered by this job

Fully remote

Flexible scheduling

Short onboarding

Hourly pay up to $80

Job summary

prolificacademicltd is seeking Senior AI/ML engineers to contribute to large language model training and evaluation through paid, task-based studies. You will audit, rate, and refine model outputs, applying deep technical expertise to ensure high-quality human feedback for alignment and evaluation pipelines.

The role emphasizes production ML experience, proficiency with transformers, and hands-on work with RLHF/RAG in a fully remote setting with flexible scheduling.

Qualifications

• Advanced degree in CS/AI/quantitative field with ML focus.
• Production experience building, deploying, or fine-tuning ML models.
• Strong grasp of neural network architectures (Transformers, CNNs, RNNs) and optimization.
• Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG).
• Ability to audit complex model logic and assess training-data quality.
• Attention to hallucinations, biases, and logical failures in AI outputs.

Responsibilities

• Review AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy.
• Audit ML code and notebooks for training loops, preprocessing scripts, and evaluation routines; flag inefficiencies and bugs.
• Deliver structured RLHF feedback to improve model safety and helpfulness.
• Trace how a model navigates chain-of-thought prompts and identify reasoning breakdowns.
• Benchmark outputs against defined technical taxonomies and metrics.

Skills

Transformers

Neural architectures

Prompt engineering

RLHF

RAG

Model auditing

Evaluation

Problem solving

Education

BS/MS/PhD in CS/AI/Robotics

Tools

PyTorch

TensorFlow

Keras

Hugging Face Transformers

AWS SageMaker

Google Vertex AI

Weights & Biases

LangChain

Pinecone

Milvus/Weaviate

Job description

Role overview

Senior AI and machine learning engineers in the Indianapolis area can contribute to large language model training and evaluation through this paid, task-based participant opportunity. Participants apply deep technical expertise to audit, rate, and refine model outputs on a per-study basis. The core mission is supplying the high-quality human feedback that modern alignment and evaluation pipelines require.

Responsibilities

• Review AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy
• Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation routines, flagging inefficiencies and bugs
• Deliver structured feedback that fuels reinforcement learning from human feedback (RLHF) workflows aimed at improving model safety and helpfulness
• Trace how a model navigates chain-of-thought prompts and pinpoint where its reasoning breaks down
• Benchmark competing model outputs against defined technical taxonomies and performance metrics

Requirements

• BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative discipline with a machine learning focus
• Production experience building, deploying, or fine-tuning ML models
• Solid grasp of neural network architectures such as Transformers, CNNs, and RNNs, along with optimization techniques
• Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) systems
• Capacity to audit complex model logic, detect training-data contamination, and assess the mathematical foundations of ML algorithms
• Keen 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 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

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 quick onboarding
• Most tasks are designed to fit within roughly one hour of uninterrupted work, with many being shorter