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About the Role We are looking for a hands-on AI/ML Engineer who can take an idea from concept to deployment. You will be responsible for designing, developing, training, testing, and integrating machine learning models…
Intern on Shopee's Data Infrastructure OLAP team, helping develop, optimize, and maintain big data engines such as Presto/Trino, ClickHouse, StarRocks, Druid, and HBase, tuning performance and troubleshooting for stability. Core stack: Java/C++/Go/Python, SQL, big data components, and Kubernetes.
Responsibilities • Working with relevant business stake holder, explore, design and validate data products solutions including transformation and visualization to improve business productivity and new opportunities; •…
Embedding Cluster Engineer: Cloud Infrastructure Specialist Summary We are seeking an experienced Cluster Infrastructure Engineer to design, implement, and maintain our vector embedding infrastructure on cloud…
About the Relay Team At Relay, we are redefining test automation by building an AI-powered platform composed to deliver an outstanding experience across the entire software testing spectrum. Spanning functional testing…
Senior Software Engineer building the data flywheel platform that turns world-scale fleet data into training data and powers foundation-model training/evaluation at Wayve, using Python, distributed data processing (Ray, Spark/Databricks), and workflow orchestration.
Senior Technical Evangelist for Pure Storage's AI platform, turning its data platform tech (Portworx, Evergreen//One, Data Stream Services) into technical content, sandbox demos, reference architectures, and sales enablement. Requires deep AI-stack skills (PyTorch, vLLM, Kubernetes, RAG, vector DBs) plus Python/shell scripting, working in-office in Santa Clara or Bellevue.
Designs and builds a high-performance data platform for an AI-driven cybersecurity product, handling petabyte-scale security telemetry with streaming and batch processing.
Lead the design and deployment of AI/ML systems for cybersecurity, focusing on LLMs, RAG pipelines, and anomaly detection to analyze security telemetry and logs.
Huawei Canada has an immediate permanent opening for a Senior Principal Researcher. About the team: The Emerging Storage Lab is a research group based at Huawei Canada's Toronto Research Centre that is focused on…
一、Agent Runtime 与任务编排 ● 设计并实现 Agent 运行时——基于 Planning / Memory / Tool-use 构建高性能编排引擎，覆盖多步推理（ReAct / Plan-and-Solve）、上下文管理与状态机，让 Agent 稳定跑完长链路任务而不中途跑飞 ● 深度优化 Function Calling 并基于 MCP（Model Context Protocol）构建可扩展工具链，打通…
Gig-style engagement: ML/AI engineers join Prolific's Expert Network as paid participants to train and evaluate LLMs — auditing model reasoning, ML code, and RLHF quality via flexible hourly tasks paying up to $80/hr. Core tech: Python, PyTorch/TensorFlow, Hugging Face Transformers, RLHF/RAG workflows.
Paid participant gig via Prolific's Expert Network: senior AI/ML engineers work remotely to train and evaluate LLMs — auditing model reasoning and code, refining RLHF feedback, and benchmarking outputs — earning up to $80/hour. Core stack: Python, PyTorch/TensorFlow, Hugging Face, RLHF/RAG workflows.
Prolific is recruiting senior AI/ML engineers as paid participants in its Expert Network to train and evaluate LLMs: auditing model logic and ML code, providing RLHF feedback, and benchmarking outputs. Core stack: Python, PyTorch/TensorFlow, Hugging Face, RLHF/RAG workflows; pays up to $80/hour, remote from Austin, US.
Join Prolific's Expert Network as a paid participant helping train and evaluate LLMs: reviewing model architecture explanations, auditing ML code/notebooks, providing RLHF feedback, and benchmarking model outputs. Requires strong Python and PyTorch/TensorFlow skills plus LLM experience; pays up to $80/hour, remote (Belfast, UK).
Senior AI/ML engineers join Prolific's Expert Network as paid remote participants to train and evaluate LLMs — auditing model logic and code, providing RLHF feedback, and assessing chain-of-thought reasoning. Requires deep learning expertise (PyTorch/TensorFlow, Python, RLHF/RAG); pays up to $80/hour.
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 reasoning. Work is remote with flexible hours using PyTorch/TensorFlow, Python, and Hugging Face tooling, paying up to $80/hour.
Paid participant role on Prolific's Expert Network: senior AI/ML engineers train and evaluate LLMs by auditing model logic and ML code, giving RLHF feedback, analyzing reasoning, and benchmarking outputs, earning up to $80/hour on flexible remote tasks. Core stack: Python, PyTorch/TensorFlow, Hugging Face, and MLOps/RAG tooling.
AI/ML engineers join Prolific's Expert Network as paid participants to train and evaluate LLMs — auditing model reasoning and code, refining RLHF feedback, and benchmarking outputs — working remotely from the UK at rates up to $80/hour. Core stack includes Python, PyTorch/TensorFlow, Hugging Face, and cloud MLOps tools.
Join Prolific's Expert Network as a paid AI/ML participant who trains and evaluates LLMs: auditing AI-generated code and model explanations, providing RLHF feedback, analyzing model reasoning, and benchmarking outputs. Requires deep Python and PyTorch/TensorFlow skills plus LLM workflow experience (prompting, RLHF, RAG).
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