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AI & Machine Learning Engineer - AI Training About Prolific Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world. Over 35,000 AI developers,…
Gig-style AI training work through Prolific's Expert Network: experienced ML engineers get paid per task (up to $80/hour) to evaluate and train LLMs — auditing model reasoning, ML code, and RLHF feedback. Core tech: Python, PyTorch or TensorFlow/Keras, Hugging Face, plus RLHF/RAG workflows and MLOps tooling.
Paid AI-training work as a participant in Prolific's Expert Network: senior ML engineers train and evaluate LLMs by auditing model logic, code, and chain-of-thought reasoning, and providing RLHF feedback. Core stack is Python, PyTorch/TensorFlow, Hugging Face, and LLM workflows like RLHF and RAG.
Gig-style role in Prolific's Expert Network: senior AI/ML engineers get paid (up to $80/hour) to train and evaluate LLMs — auditing model reasoning, ML code, and providing RLHF feedback. Core stack includes Python, PyTorch/TensorFlow, Hugging Face, and RAG/RLHF workflows.
A paid participant role in Prolific's Expert Network: ML/AI engineers get paid hourly (up to $80/hr) to train and evaluate LLMs — auditing model reasoning and ML code, and providing RLHF feedback. Requires deep ML expertise with PyTorch or TensorFlow, Python, and hands-on LLM workflows (prompt engineering, RLHF, RAG).
ML engineers join Prolific's Expert Network as paid participants to train and evaluate LLMs remotely — auditing AI-generated explanations and code, refining RLHF feedback, and benchmarking model outputs for up to $80/hour on flexible tasks. Core stack: Python, PyTorch/TensorFlow, Hugging Face, and cloud/MLOps tools like SageMaker and Vertex AI.
Paid gig-style role joining Prolific's Expert Network as a participant: train and evaluate LLMs by auditing model reasoning, reviewing ML code/notebooks, and providing RLHF feedback. Requires solid ML engineering background (PyTorch/TensorFlow, Python, LLM workflows like RLHF/RAG); remote, task-based work paying up to $80/hour.
Senior AI/ML engineers join Prolific's Expert Network as paid participants to train and evaluate LLMs: auditing model logic and code, providing RLHF feedback, analyzing reasoning, and benchmarking outputs for up to $80/hour. Stack includes Python, PyTorch/TensorFlow, Hugging Face, cloud MLOps tools, and vector databases.
Gig-style AI training work: accepted applicants join Prolific's Expert Network as paid participants who evaluate LLM outputs, audit ML code and reasoning, and provide RLHF-style human feedback. Requires deep ML expertise (PyTorch/TensorFlow, Python, RAG/RLHF) and pays up to $80/hour on flexible tasks.
Join Prolific's Expert Network as a paid AI/ML expert who trains and evaluates LLMs: reviewing model architecture explanations, auditing ML code and notebooks, providing RLHF feedback, and benchmarking model outputs. Core stack: Python, PyTorch/TensorFlow, Hugging Face, cloud MLOps tools. Pay up to $80/hour on flexible remote tasks.
Senior AI/ML engineers join Prolific's Expert Network as paid participants to train and evaluate LLMs: auditing AI-generated technical content and ML code, providing RLHF feedback, and benchmarking model reasoning. Core stack is Python, PyTorch/TensorFlow, Hugging Face, and RAG/RLHF tooling, paid up to $80/hour on flexible remote tasks.
Paid participant gig on Prolific's Expert Network: senior AI/ML engineers train and evaluate LLMs remotely — auditing model reasoning and ML code, refining RLHF feedback, and benchmarking outputs — for up to $80/hour. Core stack: PyTorch or TensorFlow, advanced Python, Hugging Face, RAG/RLHF workflows.
Senior DevOps engineer bridging core infrastructure, security, QA, and developer teams: provides 24x7 infra/app support, manages all infrastructure as code, onboards apps through production-readiness reviews, closes observability gaps, and leads outage RCA. Core stack includes AWS, Kubernetes/OpenShift, Docker, Helm, Terraform, CI/CD, and monitoring tools.
Lead the design and implementation of advanced AI solutions for cybersecurity and digital transformation. You will develop complex predictive models, define MLOps architectures, and mentor technical teams using Python, TensorFlow, PyTorch, and Big Data technologies within an applied research environment.
• Proposed designation Manager • Role type Individual contributor. • Reporting to Director • Geo to be supported Internal - India Work timings Flexible (9:30am to 6:00pm The position in discussion is with the IT team…
**This position does not offer visa transfer or sponsorship now or in the future** Life. Unlimited. At Smith+Nephew we design and manufacture technology that takes the limits off living. Join the Smith+Nephew AI Center…
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