AI Engineer

• Build and ship Android features using Kotlin.
• Create clean mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product and design to simplify complex user journeys.
• Integrate backend APIs and ensure mobile flows are stable, secure and reliable.
• Improve app performance, crash rate, loading states, responsiveness and memory usage.
• Use analytics, user behaviour and production issues to improve the product.
• Build AI-assisted mobile experiences only where they genuinely improve the user journey.

Mobile Application Developer – AI Finance Agent

Machine Learning Engineer

• Evolve the Interactive Learning Plugin's recommendation system
• Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations.
• Build and operate applied models
• Develop, validate, version, monitor, and iterate on models used by the recommendation system.
• Define what recommendation quality means
• Develop offline, online, and longitudinal measures of recommendation performance.
• Ship incremental improvements
• Use the data and infrastructure available today while identifying the instrumentation and platform capabilities needed tomorrow.
• Partner across disciplines
• Work closely with software engineers & data analysts to productionize models and integrate them safely into the recommender service.
• Partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis.

Senior Machine Learning Engineer, Developer Advocacy

• Drive the AI Agenda: Identify, scope, and drive large-scale AI initiatives and strategic "bets" that transform how we handle claims across the Nordics.
• Pragmatic Implementation: Help set the strategy for democratizing AI internally by designing and deploying agile, low-code solutions and local agents to optimize daily workflows.
• Cross-Functional Collaboration: Act as the connective tissue between business units, data science teams, and IT to move AI concepts from ideation to production, including sustainable operations and maintenance.
• Guardrails & Best Practices: Ensure that AI tools and agents are implemented responsibly, securely, and in alignment with enterprise governance.

AI Adoption and Transformation Lead

• Build core ML systems that power a proactive AI product
• Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• Turn research ideas into working systems that run reliably in production
• Collaborate closely with research, product, and engineering teams
• Mentor other ML engineers through example and technical judgment

Senior Machine Learning Engineer

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Member of Technical Staff, Machine Learning

• Help design, build, maintain and secure scalable AI services used across SEB
• Work close to real use cases from ideas and experimentation to production-ready services
• Navigate ambiguity and turn uncertainty into progress
• Contribute to a test-and-learn culture and deliver robust solutions to complex problems

• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets.
• Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle.
• Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding.
• Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
• Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
• Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Staff AI Engineer

• Build customer-facing and internal product features end to end.
• Develop web flows, backend APIs, admin tools, dashboards and operational systems.
• Support products across insurance, payments, savings, investing, travel and financial services.
• Work with product, design, mobile and operations teams to launch fast.
• Integrate APIs, handle data flows and improve production reliability.
• Use analytics, feedback and production issues to improve features after launch.
• Help build tools that reduce manual work and improve speed across the business.

Full Stack Software Engineer – AI Neobank App

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
• Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
• Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence.
• Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
• Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
• Turn manual processes into reliable AI-enabled systems that can scale.

Applied AI Engineer

• Build AI-powered workflows, assistants, agents and automation systems.
• Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools.
• Work with product and engineering teams to turn manual processes into scalable AI-native systems.
• Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems.
• Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable.
• Prototype quickly, test with users or operators, then productionize what works.
• Improve speed, quality and consistency across workflows using AI where it creates real business value.

Applied AI Engineer – AI Neobank App

Mobile Developer – AI Neobank App

• Be accountable for the execution of the AI strategy in PAM, driving outcomes, adoption and continuous improvement
• Own the AI tool offering for PAM, ensuring the needs of the organisation are understood, documented and met with the right solutions
• Set goals and KPIs for AI usage and outcomes within PAM, tracking data on costs, adoption rates and productivity improvements
• Act as the primary point of contact for all AI-related questions and suggestions — both within PAM and across other Tech departments — driving common agendas and joint evaluations
• Build and enable a community of internal AI ambassadors and technical experts, fostering an AI-first culture that inspires, trains and supports all team members
• Run trials and assess new tools, maintaining market awareness and distinguishing between hype and realisable value
• Own a PAM catalogue of approved and recommended MCPs and Skills, keeping it current and relevant
• Safeguard AI tool usage in collaboration with Group Security, maintaining a healthy balance between productivity and security
• Organise Geek Sessions and other training initiatives to build AI capability across the department
• Collaborate cross-functionally with other Tech departments to share lessons learned and run joint efforts

PAM AI Lead

• Utveckla och produktionssätta AI- och ML-lösningar i enterprisemiljö end-to-end
• Ta ansvar för hela AI-livscykeln: från behov och lösningsdesign till drift och vidareutveckling
• Utvärdera, välja och kombinera verktyg, plattformar och tekniker utifrån situation och behov
• Arbeta med Microsoft Foundry (inkl. OpenAI, AI Services/Foundry Tools), Azure Databricks, OpenShift (Kubernetes) och DevOps-pipelines
• Samarbeta nära verksamheten för att identifiera rätt problem att lösa och säkerställa att lösningarna skapar affärsnytta i verksamheten

• As a AI/ML Engineer at Rebtel you will define how AI is done at Rebtel.
• What tooling we standardise on, how we evaluate models we put in front of real users, what "good" looks like for our prompts and our pipelines.
• AI is going from a side project to the core of how Rebtel operates and what we ship to our users.
• We're hiring the second engineer on our ML/AI subteam to help build it classical ML for the business, LLM-powered systems for the product, and a clear production mindset on both.
• You'll sit inside the Data team, report to our Head of Data, and partner with one other ML/AI engineer to shape this capability from the ground up.
• You'll own work across two complementary tracks, and you'll ship in both.
• Classical ML, in production, for operational leverage
• Risk and fraud models across payments, top-ups, and account behaviour
• Churn prediction and retention modelling on a user base of a million-plus
• Forecasting, pricing, segmentation, and the next batch of operational problems we haven't tackled yet
• Owning models end-to-end scoping with stakeholders, building, deploying, monitoring, retraining LLMs and AI agents, from internal automation to in-product features
• Start with our customer support agents and automations: RAG pipelines, prompt orchestration, tool-use, evaluation harnesses
• Move LLM capability into the product as user-facing features
• Help guide the company on where AI actually creates leverage, what to build, what to buy, what to ignore and turn the good ideas into shipped systems.

Machine Learning Engineer jobs in Sweden

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Mobile Application Developer – AI Finance Agent

Senior Machine Learning Engineer, Developer Advocacy

AI Adoption and Transformation Lead

Senior Machine Learning Engineer

Member of Technical Staff, Machine Learning

AI Engineer

Staff AI Engineer

Full Stack Software Engineer – AI Neobank App

Applied AI Engineer

Applied AI Engineer – AI Neobank App

Mobile Developer – AI Neobank App

PAM AI Lead

AI Engineer

AI/ML Engineer