Jobs at Shift Technology

Build and deploy data processing pipelines for fraud detection and AI products. Conduct R&D in machine learning, NLP, image analysis, trend analysis, and chatbots. Collaborate with clients, support prospect demonstrations, incorporate feedback, and contribute across the complete data science product lifecycle. The six-month internship requires a master’s student with production coding experience, fluent French, English communication skills, and an internship agreement.

Build and deploy an AI platform feature involving LLMs and agentic workflows for fraud detection or payment integrity. Responsibilities include researching approaches, designing solutions, developing and integrating features, evaluating precision, recall, and latency, and deploying systems to production with cross-functional teams.

Six-month QA engineering internship focused on replacing manual quality assurance bottlenecks with intelligent tooling. The intern will build and deliver an AI-driven project involving release validation, test gap analysis, synthetic test data, or environment provisioning. Responsibilities include developing production-use tooling, validating it against real releases, documenting results, and presenting to leadership while collaborating with QA, Engineering, and Product teams.

Six-month full-stack engineering internship building an internal tool for Data Scientists. The intern will gather requirements, design and develop a React front end, create C# back-end services that validate inputs and generate JSON configuration files, collaborate with Product and UX, collect feedback, deploy the tool, and maintain it. The role requires current enrollment in Computer Science or Software Engineering, React and/or C# skills, object-oriented programming knowledge, fluent English, and a university-signed internship agreement.

Support data processing pipeline deployment, including data reception, cleaning, information extraction, and fraud-model calibration. Conduct R&D in machine learning, NLP, image analysis, trend analysis, and chatbots. Collaborate across sales, legal, product, and engineering throughout the AI product lifecycle.

Support deployment and maintenance of fraud-detection solutions: assist with ETL configuration, detection implementation, feature rollout, pipeline optimization, and cross-team client engagement under senior data scientists.

Lead end-to-end delivery of AI SaaS products for insurance clients. Responsibilities include scoping projects, managing client relationships, defining methodologies, validating requirements, coordinating technical teams, aligning roadmaps and release plans, managing risks and milestones, supporting presales, and improving internal delivery processes. The role is hybrid in Paris and requires advanced French, business-fluent English, and at least five years of IT project management experience.

Build and productionize data pipelines and LLM-based, multimodal AI solutions for insurance use cases. Develop agentic AI applications using RAG, embeddings, prompting, custom tools, and evaluation frameworks. Apply responsible-AI practices, deploy and monitor machine learning systems, and lead client workshops to translate business needs into technical solutions and roadmap priorities.

Leads global sales performance and operations for an enterprise SaaS organization. Responsibilities include pipeline inspection, forecasting, deal desk management, sales methodology enforcement, KPI development, enablement, performance management, quota and territory planning, incentive design, Salesforce execution, quote-to-cash optimization, and executive reporting. Partners with the CRO and global sales leadership to improve execution across complex, long-cycle enterprise deals.

Set technical direction across engineering squads, leading Azure architecture, API management, cloud reliability, observability, infrastructure, and developer experience. Design standards and reusable frameworks for agentic AI, chatbots, MCP integrations, security, token-cost governance, and scalable product capabilities. Mentor teams, align engineering and data science, and drive modernization through robust APIs, event-driven systems, and maintainable AI ecosystems.

Build and deploy production ML solutions for fraud detection, AML and claim automation. Implement data pipelines from client extracts to the data warehouse, develop/tune/test models, automate business tasks in C#, report KPIs, and engage with clients and stakeholders.

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The internship involves setting up data processing pipelines, collaborating with clients, conducting R&D, supporting sales, and understanding product lifecycles in AI for insurance.

As a Data Scientist, you'll work on fraud detection and automation, developing models, coding, and interacting with clients while handling diverse data types.

Build and deploy data processing pipelines (batch and real-time), clean and extract information, calibrate fraud detection models, collaborate with clients, and conduct R&D on machine learning, NLP, and image analysis to drive product innovation.

The internship involves deploying data processing pipelines, collaborating with clients, conducting R&D in AI and data science, and supporting sales efforts.