At a Glance
- Tasks: Train and evaluate cutting-edge AI models while providing valuable feedback.
- Company: Join Prolific, a leader in human data for AI training.
- Benefits: Earn up to $80 per hour with flexible hours and remote work options.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Make a real impact on the future of AI technology.
- Qualifications: Experience in ML model development and deep learning expertise required.
The predicted salary is between 64000 - 84000 £ per year.
Prolific is building the biggest pool of quality human data in the world, and we need AI and Machine Learning Engineers to help train and evaluate the next generation of LLMs. If you have the necessary experience, we’ll administer a short test to assess your skills and suitability for AI tasks. Successful candidates will be invited to join Prolific as participants, where they’ll get paid for training and evaluating powerful AI models.
What you’ll bring
- Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
- Professional Experience: experience building, deploying, or fine‑tuning ML models in a production environment.
- Deep Learning Mastery: professional‑level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
- LLM Specialization: hands‑on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval‑Augmented Generation) workflows.
- Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
- Analytical Critique: high attention to detail in spotting hallucinations, biased outputs, or logical failures in AI–generated technical content.
What you’ll be doing in the role
- Evaluate LLM Architecture Logic: review AI‑generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
- Audit Code & Notebooks: validate ML‑specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
- Refine RLHF Frameworks: provide high‑quality human feedback necessary to align models with human intent, safety, and helpfulness.
- Analyze Model Reasoning: critically assess how an AI model navigates complex chain‑of‑thought prompts and identify where the reasoning breaks down.
- Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.
Key Technologies
- Frameworks: expert proficiency in PyTorch or TensorFlow/Keras.
- Language & Data: advanced Python (NumPy, Pandas, Scikit‑learn) and experience with Hugging Face Transformers.
- Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
- Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.
Benefits
Competitive pay rates (up to $80 per hour), flexible hours, ability to work from home, and the opportunity to influence AI models through professional feedback.
AI Engineer/ML Engineer - Senior Developers - AI Training - Nottingham, UK employer: Prolific
Prolific is an exceptional employer for AI and Machine Learning Engineers, offering competitive pay rates of up to $80 per hour and flexible working hours that allow for a healthy work-life balance. Located in Nottingham, the company fosters a collaborative and innovative work culture where employees can significantly influence the development of cutting-edge AI models while enjoying opportunities for professional growth and remote work flexibility.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer/ML Engineer - Senior Developers - AI Training - Nottingham, UK
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or neural networks. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of model architectures and optimisation techniques. Practice coding challenges related to ML and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Engineer/ML Engineer - Senior Developers - AI Training - Nottingham, UK
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of AI Engineer/ML Engineer. Highlight your experience with ML models, deep learning architectures, and any relevant projects that showcase your skills in AI training.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for the role. Don’t forget to mention specific technologies you’ve worked with that align with our needs.
Showcase Your Projects:If you've got any personal or professional projects related to AI or ML, make sure to include them. We love seeing practical applications of your skills, especially if they involve LLMs or innovative ML techniques.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Prolific
✨Know Your Stuff
Make sure you brush up on your knowledge of neural network architectures and optimisation techniques. Be ready to discuss your experience with LLMs, Prompt Engineering, and RLHF workflows. The more specific examples you can provide from your past work, the better!
✨Showcase Your Analytical Skills
Prepare to demonstrate your ability to audit complex model logic and identify issues like training data contamination. Think of scenarios where you've spotted hallucinations or biased outputs in AI-generated content, and be ready to explain how you tackled those problems.
✨Familiarise Yourself with Key Technologies
Get comfortable with the frameworks and tools mentioned in the job description, like PyTorch, TensorFlow, and AWS. If you have experience with vector databases like Pinecone or Milvus, make sure to highlight that as well. Being able to talk about these technologies confidently will set you apart.
✨Practice Makes Perfect
Since there’s a short test involved, it’s a good idea to practice coding challenges related to ML models and data preprocessing. Use platforms like LeetCode or HackerRank to sharpen your skills. The more prepared you are, the more relaxed you'll feel during the interview!
