• Join a cutting-edge AI research initiative and help shape the next generation of frontier AI models. • Contribute technical expertise toward training and evaluating advanced AI systems. • Design challenging, real-world machine learning and natural language processing tasks. • Create high-quality reference solutions and assess AI model performance to identify reasoning gaps and improve overall capabilities. • Develop accurate reference solutions and integrate tasks into agentic development environments using **Python**. • Build executable evaluation frameworks and testing components where appropriate. • Evaluate AI model outputs for technical correctness, reasoning quality, and overall performance. • Identify capability gaps, classify model failure modes, and provide detailed written analyses. • Create and refine evaluation guidelines, scoring rubrics, and quality standards for ML and NLP tasks. • Collaborate with fellow subject matter experts to ensure consistency, accuracy, and high-quality training data.

Role Description Join a cutting-edge AI research initiative and help shape the next generation of frontier AI models. We are seeking experienced Machine Learning & NLP Experts to contribute their technical expertise toward training and evaluating advanced AI systems. This is a part-time, fully remote opportunity requiring approximately 20 hours per week. - Design challenging, real-world machine learning and natural language processing tasks covering areas such as: - Machine Learning Model Development and Evaluation - Natural Language Understanding (NLU) - Natural Language Generation (NLG) - Information Retrieval and Search - Applied Machine Learning Pipelines - Transformer Models and Large Language Models (LLMs) - Develop accurate reference solutions and integrate tasks into agentic development environments using Python. - Build executable evaluation frameworks and testing components where appropriate. - Evaluate AI model outputs for technical correctness, reasoning quality, and overall performance. - Identify capability gaps, classify model failure modes, and provide detailed written analyses. - Create and refine evaluation guidelines, scoring rubrics, and quality standards for ML and NLP tasks. - Collaborate with fellow subject matter experts to ensure consistency, accuracy, and high-quality training data. Qualifications - Deep hands-on experience in Machine Learning and/or Natural Language Processing through industry, research, or graduate/PhD-level work. - Strong proficiency in Python with practical experience developing ML or NLP applications. - Strong understanding of modern machine learning techniques, including: - Model Training and Evaluation - Transformer Architectures - Large Language Models (LLMs) - NLP Pipelines - Feature Engineering and Model Optimization - Experience with industry-standard frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or equivalent. - Ability to commit approximately 20 hours per week. - Excellent written communication skills and the ability to work independently in a remote environment. Preferred Qualifications - Experience in AI model evaluation, AI training data creation, or human-in-the-loop model assessment. - Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embedding models, or multimodal AI systems. - Experience building benchmarking frameworks, automated evaluation pipelines, or testing infrastructure. - Contributions to open-source ML/NLP projects or published research are a plus. - Experience working with production-scale machine learning systems. Role Details - Employment Type: Independent Contractor - Work Arrangement: Fully Remote - Schedule: Approximately 20 hours per week - Project Duration: Based on project requirements and performance, with opportunities for extension Equal Opportunity We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request. Contract & Payment Terms - You will be engaged as an independent contractor. - This is a fully remote role that can be completed on your own schedule. - Projects may be extended, shortened, or concluded early depending on business needs and performance. - Your work will not involve access to confidential or proprietary information from any employer, client, or institution. - Payments are made weekly via Stripe or Wise based on services rendered. - Please note: We are unable to support H1-B or STEM OPT candidates at this time.

• Partner with research and engineering teams to strengthen AI model capabilities in MLOps, ML infrastructure, and large-scale training systems. • Design challenging, real-world MLOps and machine learning systems tasks that reflect production engineering scenarios. • Develop accurate, well-documented solutions to complex ML infrastructure and training pipeline problems. • Review and evaluate technical tasks and AI-generated solutions, providing clear and actionable written feedback. • Create detailed evaluation rubrics and scoring frameworks for topics including: - Distributed training architectures - ML pipeline design - Infrastructure optimization - Kernel-level programming - Performance tuning • Collaborate with fellow subject matter experts to maintain consistency, quality, and technical accuracy across training datasets. • Contribute domain expertise to improve the reasoning capabilities of advanced AI systems.

Role Description Join a cutting-edge AI research initiative at the forefront of Generative AI and contribute to the development of next-generation Large Language Models. We are seeking experienced MLOps Engineers with deep expertise in modern machine learning frameworks, large-scale training infrastructure, and kernel-level optimization. In this role, you'll leverage your knowledge of JAX, PyTorch, and custom GPU kernel programming (Pallas/Triton) to create, evaluate, and refine high-quality technical tasks that help train frontier AI systems. You'll collaborate with AI researchers and engineering teams to improve model reasoning across MLOps, distributed training, and ML infrastructure topics. This is a full-time, 40-hour-per-week remote engagement requiring full weekday availability. Key Responsibilities - Partner with research and engineering teams to strengthen AI model capabilities in MLOps, ML infrastructure, and large-scale training systems. - Design challenging, real-world MLOps and machine learning systems tasks that reflect production engineering scenarios. - Develop accurate, well-documented solutions to complex ML infrastructure and training pipeline problems. - Review and evaluate technical tasks and AI-generated solutions, providing clear and actionable written feedback. - Create detailed evaluation rubrics and scoring frameworks for topics including: - Distributed training architectures - ML pipeline design - Infrastructure optimization - Kernel-level programming - Performance tuning - Collaborate with fellow subject matter experts to maintain consistency, quality, and technical accuracy across training datasets. - Contribute domain expertise to improve the reasoning capabilities of advanced AI systems. Qualifications - Minimum 2 years of professional experience in MLOps, Machine Learning Infrastructure, or ML Systems Engineering within a recognized technology organization. - Hands-on production experience with JAX and/or PyTorch in large-scale machine learning environments. - Practical experience developing or optimizing custom GPU kernels using Pallas (JAX) or Triton. - Strong understanding of distributed training systems, model optimization, and scalable ML infrastructure. - Demonstrated career growth and increasing technical responsibility. - Availability to work 40 hours per week during standard weekday business hours. - Excellent written communication skills with the ability to clearly explain technical concepts and architectural decisions. Preferred Skills - Experience designing and optimizing large-scale ML training pipelines. - Knowledge of distributed computing and GPU performance optimization. - Familiarity with evaluation methodologies for AI models and ML systems. - Experience collaborating with research teams on advanced machine learning projects. - Passion for advancing AI infrastructure and frontier model development. Benefits - Help build and improve next-generation Large Language Models. - Work alongside leading AI researchers and experienced machine learning engineers. - Apply your expertise to high-impact projects involving large-scale ML systems and infrastructure. - Contribute directly to the development of cutting-edge AI technologies. - Enjoy a fully remote engagement with meaningful technical challenges. Equal Opportunity We welcome applications from qualified professionals regardless of legally protected characteristics and are committed to providing reasonable accommodations throughout the application and engagement process upon request. Contract & Payment Terms - Engagement is offered on an independent contractor basis. - This is a fully remote opportunity that can be completed according to your own schedule. - Project duration may be extended, shortened, or concluded based on project requirements and individual performance. - The engagement does not require access to confidential or proprietary information belonging to any current employer, client, or institution. - Payments are processed weekly through Stripe or Wise based on approved work completed. - Please note: Applicants requiring H-1B sponsorship or participating in the STEM OPT program are not eligible for this opportunity.