Freelance Electrical Engineering & Python Expert - 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.
Freelance Machine Learning Engineer (Python)
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 of days or weeks. 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. Document problem statements clearly and provide verified correct answers.
Freelance Machine Learning AI Trainer (Python)
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.
Safety Engineer
The AI Safety Engineer is responsible for designing and building scalable backend infrastructure for content moderation, abuse detection, and agents guardrails by deploying AI/ML models into production systems. They will architect robust APIs, data pipelines, and service architectures to support real-time and batch moderation workflows. The role includes implementing comprehensive monitoring, alerting, and observability systems, establishing SLIs, SLOs, and performance benchmarks. The engineer will collaborate with ML engineers to translate research models into production-ready systems and integrate them across the product suite. Additionally, they will drive technical decisions and contribute to the vision for the safety roadmap to build next-generation platform guardrails for scale and precision.
Product Designer, Monetization
As an Applied Research Scientist on the Agents team, you will develop state-of-the-art tools for correcting, improving, and enhancing written English using various NLP, ML, and DL technologies. You will productize and ship these features into Superhuman's product offerings, used by millions daily. You will stay up-to-date with the latest research trends that could improve the product and contribute to the research strategy and technical culture of the company. Additionally, you will help attract professionals in the industry to build a best-in-class research team creating a state-of-the-art writing and communication assistant.
Software Engineer - Embedded NixOS
You will develop ML/AI that leverage and extend the latest state-of-the-art methods and architectures, design experiments and conduct benchmarks to evaluate and improve their performance in real-world scenarios, work on impactful projects, and collaborate with people across several teams and backgrounds to integrate cutting edge ML/AI in production systems.
Freelance Electrical Engineer with Python Experience - 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.
ML Engineer - NLP (m/f/d)
Take ownership for the full lifecycle of our models: design, training, evaluation, and deployment of our deep learning models in the space of speech recognition and NLP. Build and continuously improve deep learning models for speech recognition and natural language understanding that power our core product and help thousands of users. Develop and run large-scale self-supervised training pipelines, as well as low-latency inference systems for mobile devices.
Infrastructure Engineer
Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.
AI / ML Solutions Engineer
The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.
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