Automotive Engineering & Python Expert - Freelance AI Trainer
Contributors design graduate- and industry-level automotive 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.
Data Scientist (Python & SQL) - Freelance AI Trainer
As a Data Science AI Trainer at Mindrift, you will design original computational data science problems simulating real-world analytical workflows across various industries such as telecom, finance, government, e-commerce, and healthcare. You will create problems requiring Python programming using libraries like pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn. The problems must be computationally intensive and unsolvable manually within reasonable timeframes. You will develop problems involving non-trivial reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction, ensuring they are deterministic with reproducible answers and based on real business challenges like customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. You will design problems covering the entire data science pipeline from data ingestion to deployment considerations, including big data processing and scalable computational approaches. You will verify solutions using Python and document problem statements with realistic business contexts and provide verified answers.
Machine Learning Developer (Freelance)
Design original computational STEM problems that simulate real scientific workflows. Create problems that require Python programming to solve. Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches. Verify solutions using Python with standard libraries (numpy, pandas, scipy, sklearn). Document problem statements clearly and provide verified correct answers.
Forward Deployed Engineer - Strategist - Europe
As a Forward Deployed Engineer Strategist, you will work with Engineers, Product Designers, and other Strategists to deploy voice AI technology to solve customer problems. Responsibilities include meeting with strategic customers to understand their audio and voice AI needs, identifying relevant use cases through engagement with customer problems, designing and architecting custom integrations, guiding customers on best practices for AI model implementation, presenting results and proposals to technical and executive audiences, collaborating with Research and Product teams to incorporate field insights, building and delivering demos of AI technology, scoping potential applications in new industries, taking full ownership of major projects for strategic partners, and working daily with customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.
Statistics Expert (Python) - Freelance AI Trainer
Contributors may design rigorous statistics problems reflecting professional practice, evaluate AI solutions for correctness, assumptions, and constraints, validate calculations or simulations using Python libraries such as NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn, improve AI reasoning to align with industry-standard logic, and apply structured scoring criteria to multi-step problems.
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.
Freelance AI Evaluation Engineer (Python/Full-Stack)
Create challenging coding test cases that 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, not just superficial checks. Craft "fair but hard" challenges where the AI has all the context it needs but must work for it, with information scattered across files and external sources requiring complex reasoning. Analyze AI failures to understand what the model struggles with versus what it masters. Iterate based on feedback from expert QA reviewers who score work on seven quality criteria.
Mechanical Engineer & Python Expert - Freelance AI Trainer
Contributors to the projects 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.
Senior ML Operations (MLOps) Engineer
The Senior ML Operations (MLOps) Engineer at Eight Sleep is responsible for introducing and implementing cutting-edge ML technologies, owning the design and operation of robust ML infrastructure including scalable data, model, and deployment pipelines to ensure reliable model delivery to production. They collaborate cross-functionally with R&D, firmware, data, and backend teams to ensure reliable and scalable ML inference on Pods. They optimize ML systems for cost, scalability, and performance across training and inference, and develop tooling, microservices, and frameworks to streamline data processing, experimentation, and deployment. The role requires effective communication in a remote work environment.
Manual Quality Assurance Engineer, Web Core Product
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
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