AI Engineer/ML Engineer - Senior Developers - AI Training - Colorado Springs, US

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

Benefits offered by this job

Fully remote

Flexible scheduling

Project-based engagements

Job summary

Prolific Academic Ltd is seeking senior machine learning engineers to audit and evaluate cutting-edge large language models. You will work on remote, intermittent tasks that demand deep ML expertise and careful judgment about model behavior and outputs.

You will review architectures, validate training scripts, and provide structured feedback to improve RLHF alignment. Strong familiarity with Transformers and modern ML tooling is essential for this role.

Qualifications

• Degree in CS/AI/Robotics or related quantitative field with ML emphasis.
• Hands-on production experience building, deploying, or fine-tuning ML models.
• Strong grasp of neural networks including Transformers, CNNs, RNNs and modern optimizers.
• Experience with prompt engineering, RLHF, or retrieval-augmented generation.
• Proven ability to audit model behavior and detect data contamination or biased reasoning.
• Based in the Colorado Springs area.

Responsibilities

• Review AI-generated descriptions of architectures, loss functions, and backpropagation for correctness.
• Validate ML code, training scripts, and notebooks for efficiency and accuracy.
• Provide structured feedback to strengthen RLHF alignment processes.
• Probe model reasoning on chain-of-thought prompts and surface weaknesses.
• Benchmark outputs against technical taxonomies and quantitative criteria.

Skills

ML deployment

Transformer networks

Prompt engineering

RLHF

Model auditing

Bias/robustness

Education

Bachelor's/Master's/PhD in CS/AI/Robotics or related ML field

Tools

PyTorch

TensorFlow

Keras

NumPy

Pandas

Scikit-learn

Hugging Face Transformers

AWS SageMaker

Vertex AI

Weights & Biases

LangChain

Pinecone

Milvus

Weaviate

Job description

Role overview

This is a paid, flexible opportunity for senior machine learning engineers to help train and evaluate cutting-edge large language models. Participants bring rigorous technical judgment to short, focused remote assignments that audit AI reasoning, code, and outputs. The role is intermittent and fits around other professional commitments, rewarding deep expertise rather than continuous availability.

Responsibilities

• Review AI-generated descriptions of model architectures, loss functions, and backpropagation for technical correctness
• Validate ML code, training scripts, and evaluation notebooks for efficiency and accuracy
• Supply structured human feedback that strengthens RLHF alignment processes
• Probe model reasoning on chain-of-thought prompts and surface weaknesses in logic
• Benchmark model outputs against technical taxonomies and quantitative performance criteria

Requirements

• Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Robotics, or a closely related quantitative field with an ML emphasis
• Hands-on production experience building, deploying, or fine-tuning ML models
• Strong grasp of neural network architectures such as Transformers, CNNs, and RNNs, and contemporary optimization techniques
• Practical experience with prompt engineering, reinforcement learning from human feedback, or retrieval-augmented generation
• Proven ability to audit model behavior, identify training data contamination, and detect hallucinations or biased reasoning
• Based in the Colorado Springs area

Nice to have

• Deep proficiency in PyTorch or TensorFlow and Keras
• Advanced Python expertise with NumPy, Pandas, and Scikit-learn, plus Hugging Face Transformers
• Experience with AWS SageMaker, Google Cloud Vertex AI, Weights & Biases, or LangChain
• Familiarity with vector databases including Pinecone, Milvus, or Weaviate

Benefits and work setup

• Compensation typically up to $80 per hour for qualifying tasks
• Fully remote work with scheduling tied to project demand
• Single sessions generally require up to one hour of uninterrupted focus, with many tasks shorter than that