Freelance AI Evaluation Engineer (Python/Full-Stack)
Create challenging coding test cases to push AI coding systems to their limits by reviewing and refining realistic coding tasks based on provided production codebases with realistic scope, requirements, and information sources. Write comprehensive functional tests that validate actual end-to-end behavior and edge-cases. Craft challenges that are fair but hard, where the AI has all the context it needs, requiring complex reasoning with information scattered across files and external sources. Analyze AI failures to understand the model's struggles and strengths. Iterate based on feedback from expert QA reviewers who score work on seven quality criteria.
Mathematics Researcher (Python) - Freelance AI Trainer
Contributors may design rigorous mathematics problems reflecting professional practice, evaluate AI solutions for correctness, assumptions, and constraints, validate calculations or simulations using Python (NumPy, Pandas, SciPy), improve AI reasoning to align with industry-standard logic, and apply structured scoring criteria to multi-step problems.
AI & IT Systems Engineer
As Jasper undergoes an agentic AI shift, the AI & IT Systems Engineer role involves ensuring the IT infrastructure is robust, secure, and fine-tuned for advanced AI workflows, spending 70-80% of time on AI enablement deployments. Responsibilities include modernizing and improving IT systems to support autonomous AI workflows, building scalable automation infrastructure to enhance efficiency and reduce manual tasks, and operationalizing AI initiatives using tools like Claude, ChatGPT, and Zapier to create intelligent, cross-platform workflows involving platforms like Google Workspace and Slack. The role also requires managing core IT systems such as Identity Providers and Mobile Device Management, streamlining identity and access operations using features like Okta Workflows, and providing cross-functional technical support across departments to implement AI enablement projects. Additionally, the engineer manages a broad SaaS ecosystem, including Google Workspace and Linear, and assists in developing training resources and playbooks to facilitate team adoption of new AI tools.
Senior Machine Learning Engineer
Lead the exploration and application of Large Language Models and Generative AI, focusing on new areas within these fields. Translate the latest research into high-performing systems and models that can enhance user experiences. Help set the team's strategic direction, fostering an environment that encourages innovation and professional growth. Actively engage in all aspects of development including ideation, experimentation, implementation, and deployment. Collaborate with various teams and product managers to develop and implement ML-based solutions, ensuring performance optimization and alignment with broader business goals.
Data Scientist, Growth
The Data Scientist, Growth at Eight Sleep is responsible for leading complex forecasting challenges that impact supply chain, marketing spend, and business growth. This includes building advanced demand forecasting models to prevent stock-outs during peak periods and avoid overcommitting capital on inventory, developing marketing spend optimization algorithms that factor in seasonality, macro trends, and cross-channel effects, creating experimentation frameworks for incrementality testing across marketing channels like Meta, Google, and YouTube with statistical rigor, and designing marketing attribution models to handle complex customer journeys and multi-touch attribution challenges.
Senior Brand Events Manager
Own the observability and lifecycle management of AI features across the organization. Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features. Design and implement closed-loop evaluation pipelines that automatically validate prompt changes. Develop comprehensive metrics and dashboards to track LLM usage: cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls. Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring. Collaborate with engineering teams across the organization to ensure they have the tools and visibility needed to build high-quality AI features.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors may design graduate- and industry-level mechanical engineering problems grounded in real practice. They evaluate AI-generated solutions for correctness, assumptions, and engineering logic. They validate analytical or numerical results using Python (NumPy, SciPy, Pandas). They improve AI reasoning to align with first principles and accepted engineering standards. They apply structured scoring criteria to assess multi-step problem solving.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors in this project design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python with libraries such as NumPy, SciPy, and Pandas, improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python (NumPy, SciPy, Pandas), improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors design graduate- and industry-level mechanical engineering problems grounded in real practice, evaluate AI-generated solutions for correctness, assumptions, and engineering logic, validate analytical or numerical results using Python libraries such as NumPy, SciPy, and Pandas, improve AI reasoning to align with first principles and accepted engineering standards, and apply structured scoring criteria to assess multi-step problem solving.
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