AI Jobs in Paris

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As an AI Infrastructure Engineer at Together, the responsibilities include participating in on-call rotation to respond to production incidents, building and running infrastructure using Ansible, Terraform, and Kubernetes to support scaling to a large number of concurrent users, building monitoring systems to ensure high-quality service, designing and implementing operational processes such as deployments and upgrades, debugging production issues across all services and stack levels, identifying improvements for product architecture in terms of reliability, performance, and availability, and planning the growth of Together AI's infrastructure.

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Translate cutting-edge research into production-ready machine learning systems. Design, build, and deploy end-to-end ML models and pipelines. Develop and optimize models for image and video processing. Own the full ML lifecycle including experimentation, training/fine-tuning, evaluation, and deployment. Rapidly prototype using open-source models and adapt them for product needs. Conduct experiments, analyze results, and iterate to improve performance. Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale. Participate with advancements in machine learning and apply them to continuously improve products.

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Utilize proprietary software to provide accurate input and labels for healthcare and administration projects, ensuring high-quality data for AI model training. Deliver curated, high-quality data for scenarios involving patient care coordination, medical billing, administrative workflows, and healthcare operations. Collaborate with technical staff to support the training of new AI tasks and contribute to the development of innovative technologies. Assist in designing and improving efficient annotation tools tailored for healthcare and administration data. Select and analyze complex problems in healthcare and administration fields aligned with your expertise to enhance AI model performance. Interpret, analyze, and execute tasks based on evolving instructions, maintaining precision and adaptability.

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Conduct structured process interviews with leads across Finance, Legal, HR, Operations, and Business / Revenue to map recurring, high-cognitive-load tasks. Identify which tasks are suitable for Claude skill encoding — well-defined inputs, predictable structure, clear success criteria. Write, test, and iterate Claude skills: system prompts, instructions, behavioral rules, few-shot examples, output formats, and edge case handling. Validate each skill directly with end users until it performs reliably for non-technical team members. Maintain a documented skill library with scope, usage guide, known limitations, and update log for each skill. Build and share a reusable methodology for skill writing that other teams can apply independently after the internship.

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Collaborate with the AI Tools squad to implement and improve AI features in the Photoroom app, including Logo maker, AI Images, AI Videos, and other features on the app homepage. Design and architect new features by chaining a mix of internal and external services to generate images and videos for users. Monitor and scale the growing load on the FastAPI service using Datadog to find optimizations and bottlenecks or implement smart caching of pipeline steps.

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Contributors generate prompts that challenge AI, evaluate AI-generated solutions for correctness, assumptions, and logic, improve AI reasoning to align with first principles and accepted standards, and apply structured scoring criteria to assess multi-step problem solving.

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As an AI Deployment Strategist, responsibilities include driving the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation. Leading executive-level workshops to identify business challenges and opportunities, co-creating AI adoption roadmaps with customers, and partnering with Account Executives to develop business cases. Architecting end-to-end AI solutions by integrating Mistral’s models and platform into customer workflows and technical infrastructure, collaborating with the Applied AI team to design, prototype, and deploy scalable AI solutions in production. Owning pilots and proofs-of-value, demonstrating technology potential and enabling full-scale deployments. Serving as a trusted advisor to guide customer AI strategy, monitoring outcome-driven KPIs, and identifying expansion opportunities within accounts. Acting as a liaison between customers and Mistral’s internal teams to influence product and research roadmaps, creating reusable assets and best practices to scale go-to-market efforts, and traveling 30–60% to support client relationships and on-site deployments. Additionally, translating industrial engineering challenges into AI use cases, designing hybrid AI-physics pipelines validated against ground truth simulations, navigating enterprise IT constraints including deployment in air-gapped environments or on-prem HPC clusters, and conducting hands-on workshops with engineers to upskill teams on AI-assisted workflows.

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Understand and identify the customer’s most important and impactful multi-step task to automate. Seamlessly integrate with customer systems, including but not limited to databases, third-party APIs, and internal tools. Rapidly iterate in the field with tight feedback loops to continuously improve product fit and drive end-to-end solution delivery. Architect, build, and maintain production-grade services that scale with usage and complexity. Collaborate closely with product, research, and engineering teams to shape the roadmap and align on priorities based on findings in the field.

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As a psychometrician intern, you will help design, validate, and improve AI-powered assessments, working at the crossover between psychometrics and machine learning. Your day-to-day duties include building and validating psychometric assessments designed for AI integration, running analyses on item quality, fairness, reliability, and scoring accuracy, helping develop and refine automated scoring algorithms, exploring how large language models (LLMs) can be used to generate and evaluate assessment content, translating findings into clear insights for clients and internal teams, and contributing to research reports and potentially academic publications.

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Conceptualise scripts based on current production needs centred around existing AI characters, create narrative-driven longform video content including stylized and explicit NSFW visuals with strong storytelling, atmosphere, and visual coherence, own and manage end-to-end AI video production workflows from ideation and prompting to generation, editing, and post-production, work extensively with ComfyUI pipelines building, customizing, and optimizing node-based workflows for image and video generation, utilize tools such as Stable Diffusion (AUTOMATIC1111), ComfyUI, Runway, and other AI video platforms to produce high-quality visual sequences, develop and maintain consistent character appearance, style, and scene continuity across longer narratives, integrate motion graphic design and color correction for cohesive final outputs, experiment rapidly with new AI models, tools, and techniques and share skills with the team, align with Content Lead’s creative direction while maintaining autonomy in execution and technical decisions, continuously refine workflows for efficiency, scalability, and output quality.