Automotive Engineering & Python Expert - Freelance AI Trainer
Contributors may 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 (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.
Data Scientist (Python & SQL) - Freelance AI Trainer
As a Data Science AI Trainer, responsibilities include designing original computational data science problems that simulate real-world analytical workflows across various industries such as telecom, finance, government, e-commerce, and healthcare. The role involves creating problems requiring Python programming using libraries like pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn, and ensuring these problems are computationally intensive and cannot be solved manually within reasonable timeframes. The trainer develops problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction, creates deterministic problems with reproducible answers, and bases them on real business challenges including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Responsibilities also include designing end-to-end problems spanning the complete data science pipeline, incorporating big data processing scenarios requiring scalable computational approaches, verifying solutions using Python with standard data science libraries and statistical methods, and documenting problem statements clearly with realistic business contexts and verified correct answers.
Machine Learning Developer (Freelance)
Collaborate on projects to design original computational STEM problems that simulate real scientific workflows, create problems requiring Python programming to solve, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains and creative problem-solving approaches, verify solutions using Python with standard libraries such as numpy, pandas, scipy, and sklearn, and document problem statements clearly with verified correct answers.
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.
Electrical Engineer & Python Expert - Freelance AI Trainer
Contributors may design rigorous electrical engineering 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.
Mechanical Engineer & Python Expert - Freelance AI Trainer
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. Apply structured scoring criteria to assess multi-step problem solving.
Data Quality Specialist
Generate and validate high-quality data annotations based on guidelines and continuous feedback for the development and evaluation of AI models. Collaborate with the technical team to review and audit annotations, clarify requirements, share insights, and improve annotation processes, tools, and guidelines.
Data Engineer - Foundational
As a Data Engineer on the Foundational team, you will build ETL/ELT pipelines to extract, decode, and store raw Electro-Optical (EO) and Infrared (IR) video from field logs into optimized formats like WebDataset, TFRecords, or Parquet. You will develop algorithms to synchronize EO and IR frames temporally and spatially to provide paired inputs for model training. You will architect storage-to-GPU pipelines to ensure multi-node training clusters maintain over 90% GPU utilization without I/O bottlenecks. Your role includes writing and optimizing distributed data processing jobs using tools such as Apache Spark, Ray, or Apache Beam to process thousands of hours of tactical video logs. You will implement automated quality checks to filter corrupted or blank frames and maintain reproducible training runs through robust versioning and lineage tracking. Additionally, you will assess and implement advanced storage solutions like MinIO and S3 tiering to manage growing datasets while optimizing cost and latency.
Partner AI Deployment Engineer
The Partner AI Deployment Engineer (P-ADE) leads technical delivery with OpenAI partners across EMEA to scale customer deployments built on the OpenAI platform. Responsibilities include acting as a primary technical delivery partner for OpenAI partners, supporting customer deployments across multiple industries and use cases, working with partner delivery teams and customer stakeholders to translate solution designs into deployable, production-ready architectures, supporting customer time to value through hands-on prototyping, integration support, architectural guidance, and troubleshooting during critical delivery phases. The role involves close collaboration with Solutions Engineers, Forward Deployed Engineers, and other ADEs to ensure appropriate technical expertise is engaged from design through production rollout. The engineer helps partners operationalize solutions by addressing scalability, reliability, security, and safety considerations for enterprise production environments, contributes to reusable deployment patterns, reference architectures, and delivery guidance for repeatable execution, acts as a technical quality and governance point to ensure solutions meet OpenAI's standards before and after go-live, and captures and synthesizes feedback from deployments to share insights with Applied, Research, and partner teams to improve delivery playbooks and platform capabilities.
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