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The Research Scientist will push forward the fields of AI and biology, contribute to the company's research roadmap, and lead projects in foundation models. Responsibilities include collaboration with partners, implementing software for research, and engaging in the scientific community through publications and open source releases.
As a Research Engineer, AI, you will contribute to executing the company's research roadmap by pretraining and fine-tuning foundation models for biology applications, implementing software for research initiatives, and collaborating with a multi-disciplinary team to drive projects in cutting-edge AI and biology.
The AI Solution Architect will engage in pre-sale activities, guide product implementation and integration, and ensure customer success by providing support and optimizing the product's use. This role requires technical expertise in AI solutions, customer-facing communication, and project management skills.
The AI Scientist will modify and fine-tune large language models for human interaction, design annotation processes, participate in pre-training efforts, and navigate the MLOps stack. They will also have hands-on experience with AI frameworks and work with distributed systems while collaborating within a team.
The Applied AI Engineer will onboard customers for Mistral AI's products, work on GenAI applications, manage multi-stakeholder relations, assist in deployment of AI solutions, and collaborate with the team to enhance product offerings, focusing on fine-tuning LLMs and ensuring effective integration.
Senior Cloud Engineer responsible for building a highly available, global, multi-cloud PaaS platform for AI workloads. Must have experience with infrastructure-as-code, cloud microservices architectures, Kubernetes, and software development fundamentals.
AI Researcher responsible for developing novel architectures, system optimizations, and algorithms to push the frontier of open models. Collaborate with cross-functional teams and stay updated on the latest advancements in machine learning. Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or related field required.
The Software Engineer for AI Integrations will design and implement integrations with various LLM APIs, develop robust API wrappers, create intelligent automation tools, and optimize AI service integrations. Responsibilities include collaboration with product teams, monitoring development, and technical documentation.
Featured Jobs
As a Senior Software Developer at Bandwidth, you'll lead the Advanced Analytics team in managing streaming analytics and AI/ML applications, collaborate with cross-functional teams to deliver solutions, and take on architectural responsibilities while mentoring junior data scientists.
In this role, you will develop tech roadmaps for Large Language Models, focusing on LLM deployment and integration into AI products. Responsibilities include designing and optimizing LLM-based systems, fine-tuning models, and integrating with Agentic platforms. You will work with cross-functional teams to drive AI initiatives aligned with business objectives.
The Data and AI Architect will design and implement data-driven solutions and AI models, focusing on the Salesforce platform. Responsibilities include developing data architectures, leading machine learning projects, enforcing data governance, collaborating with cross-functional teams, and mentoring staff, while ensuring compliance with data regulations.
As an AI Quantitative Strategist at WorldQuant, you will develop and implement AI/ML models for trading optimization and investment strategies. You will work collaboratively on innovative projects while leveraging state-of-the-art data and systems. The role emphasizes building infrastructure for AI and involves explaining model business value to stakeholders.
The Senior AI Engineer at BuildOps will design, develop, and deploy machine learning models while enhancing AI features in a software platform. Responsibilities include data analysis, collaboration with teams, and providing technical mentorship. The role demands strong expertise in AI, machine learning, and software development, particularly in Python and Javascript.
The Fullstack AI Engineer will develop and implement AI solutions, integrate AI/ML capabilities into the platform, write scalable code, collaborate with QA, and provide technical guidance. The position involves prototyping, maintaining AI features, and promoting best practices in documentation and testing.
The AI Research Engineer will enhance the performance of the Sonar models using supervised and reinforcement learning. Responsibilities include managing data, training, and evaluation pipelines, and integrating models with engineering teams to deliver state-of-the-art query answering capabilities.
The AI Research Engineer will contribute to the development of AI capabilities within the answer engine, focusing on optimizing LLMs through innovative prompting and training. The role involves collaboration with product engineers to enhance user experience and deliver accurate responses.
As an AI Engineer & Researcher, you'll optimize model inference, build production serving systems, and accelerate research on scaling compute, contributing to AI systems that accurately understand the universe.
The AI Safety Engineer will focus on identifying safety shortcomings, designing evaluations to assess risks, implementing ML safety methods, collaborating with teams to ensure safety in development, and innovating new safety solutions for AI systems.
The AI Software Engineer will develop and integrate LLM-based features into products, improve code quality and performance, and collaborate with a multidisciplinary team to enhance user experience.
The Software Engineer will architect, build, and design a data collection platform, implement features to enhance user experience, and ensure system security and scalability. Responsibilities include monitoring data quality and contributing to innovative solutions that support AI research and model performance.
As an AI Engineer & Researcher at xAI, you will build end-to-end features, establish monitoring systems for data quality, drive data collection projects, and innovate methods for data generation. You will collaborate with cross-functional teams to improve the AI platform while ensuring security and scalability.
As an AI Inference Engineer, you will develop APIs for AI inference, optimize ML systems, benchmark performance, enhance system reliability, and implement optimizations for LLM inference.
Forward Deployed AI Engineers work directly with end customers owning strategy and implementation. Responsibilities include designing, implementing, and maintaining robust and scalable AI-driven solutions, working with large, complex codebases, and delivering measurable impact through AI solutions.
The AI Engineer & Researcher at xAI focuses on training trillion parameter neural networks, optimizing GPU utilization, innovating inference stack, implementing state-of-the-art methods, and developing AI systems to understand the universe.
Designing and implementing evaluations for new capabilities, creating new data generation methods, experimenting with fine-tuning techniques, optimizing training data quality, innovating new ideas in AI systems.
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