Evaluation Scenario Writer - AI Agent Testing Specialist
Contributors may create structured test cases that simulate complex human workflows, define gold-standard behavior and scoring logic to evaluate agent actions, analyze agent logs, failure modes, and decision paths, work with code repositories and test frameworks to validate scenarios, iterate on prompts, instructions, and test cases to improve clarity and difficulty, and ensure that scenarios are production-ready, easy to run, and reusable.
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.
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)
As a Machine Learning expert on the Mindrift platform, you will design original computational STEM problems that simulate real scientific workflows, create problems that require Python programming to solve, and ensure these problems are computationally intensive such that they cannot be solved manually within reasonable timeframes (days/weeks). You will 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 while providing verified correct answers.
Freelance Machine Learning AI Trainer (Python)
As a Machine Learning expert at Mindrift, the responsibilities include designing original computational STEM problems that simulate real scientific workflows and require Python programming to solve. Problems must be computationally intensive and unattainable to solve manually within reasonable timeframes (days/weeks), involve non-trivial reasoning chains and creative problem-solving, and require verification of solutions using Python with standard libraries such as numpy, pandas, scipy, and sklearn. Additionally, clear documentation of problem statements and provision of verified correct answers are part of the role. The work involves creating training prompts, refining model responses, and contributing to projects aligned with the candidate's skills on their own schedule within a fully remote freelance role.
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.
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.
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.
Software Engineer, macOS Core Product - Virginia Beach, USA
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core machine learning inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions addressing the highest priority issues.
Software Engineer, macOS Core Product - Rialto, USA
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to their 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 to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.