Build and implement LLM and Agentic applications through the full development cycle from ideation to evaluation. Participate in R&D initiatives and research cutting-edge AI technologies to support internal and client-facing projects.
Remote AI Engineer Jobs in Poland (96)
Search = AI Engineer
Remote in = Poland
Build and implement LLM and Agentic applications through the full development cycle from ideation to evaluation. Participate in research of cutting-edge AI technologies and contribute to internal R&D and client-facing demos.
Architect and build agentic workflows and conversational systems using LLMs and reasoning components to optimize recruiting. Lead the end-to-end development of ML/NLP products from ideation through production and deployment.
Senior Machine Learning Engineer (AI tools)
SmartRecruiters Inc
·
Full Time
·
6 Weeks Ago
SmartRecruiters Inc
Architect and build agentic workflows and conversational systems using LLMs and reasoning components to optimize recruiting. Lead the end-to-end development of ML/NLP products from ideation through production and deployment.
You will build and evolve the agent harness by implementing hooks, permission gates, and context compaction to ensure reliable task completion. Additionally, you will architect planner/executor/evaluator pipelines and manage agent memory to support long-horizon, multi-session execution.
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You will solve high-impact problems across products and internal systems by designing and implementing end-to-end AI and automation solutions. You will also influence technical direction, define best practices, and collaborate with stakeholders to integrate AI effectively into engineering workflows.
Senior Machine Learning Engineer (AI tools)
SmartRecruiters Inc
·
Full Time
·
7 Weeks Ago
SmartRecruiters Inc
You will architect and develop agentic workflows that integrate large language models and reasoning components to create adaptive conversational systems. Additionally, you will lead the end-to-end development of ML/NLP products, from ideation and model training to production deployment.
The AI Engineer will integrate Generative AI models and LLMs into web applications using efficient API design and scalable microservices. They will also manage cloud infrastructure, maintain data pipelines, and implement CI/CD processes to ensure high-performing AI deployments.
The AI Engineer will integrate Generative AI models and Large Language Models into web applications through efficient API design and microservices. They are also responsible for building robust back-end systems, maintaining data pipelines, and managing scalable cloud infrastructure.
Lead the development of a new AI-powered product from initial architecture to production-ready code. Design and build sophisticated conversational experiences and agentic workflows while setting engineering standards for the team.
Architect and develop agentic workflows that integrate large language models and reasoning components into conversational recruiting systems. Lead the end-to-end development of ML/NLP products while mentoring team members and defining best practices for scalable AI systems.
Design and maintain the core AI infrastructure, frameworks, and shared services that enable product teams to build AI-powered features. Collaborate with cross-functional teams to integrate LLMs, vector stores, and retrieval pipelines while ensuring high-quality performance and scalability.
You will architect and develop agentic workflows that integrate large language models and reasoning components into conversational recruiting systems. Additionally, you will lead the end-to-end development of ML/NLP products while mentoring team members and defining best practices for scalable AI systems.
Design and deliver complex product epics at high velocity while architecting AI-assisted guardrails across the software development lifecycle. Partner with engineering teams to implement AI-native practices and scale reusable tooling across the organization.
Design and build autonomous agentic loops to automate business workflows across various domains including listings, revenue, and customer experience. Own the full lifecycle of these agents from architecture and production deployment to monitoring and iterative improvement.
Design and implement end-to-end AI-powered features spanning React frontends, Python services, and LLM integrations, while building and maintaining components of the Agentic SDK for internal team use. Responsibilities also include developing LLM orchestration workflows and partnering with product teams to deliver technical solutions.
The Staff Software Engineer will set the multi-year technical strategy for AI platform development, partnering with senior leadership on the long-term vision and architecting foundational AI systems like LLM orchestration frameworks. They will own organization-wide technical decisions, define quality standards for AI development, and coach senior engineers toward staff-level impact.
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The role involves designing, building, and deploying production-grade Generative AI applications using LLM APIs, owning end-to-end feature delivery including backend development in Python and UI integration. Responsibilities also include implementing RAG pipelines, agentic workflows, and integrating AI workloads with security platforms and data lakes.
The role involves designing, improving, and scaling generative pipelines for image and video creation, focusing on tuning model behavior for visual quality and style consistency. Key tasks include optimizing workflows for stable production results and researching new generative models and tools.
The role involves solving high-impact problems across products and internal systems by identifying opportunities for AI or automation, and then designing and building end-to-end solutions involving LLMs and agentic workflows. A significant focus is placed on improving internal software development processes through AI-assisted systems for writing, reviewing, testing, and operating software.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. The engineer will lead the design and development of advanced ML/NLP products from concept through production, including model training, optimization, and deployment.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. Responsibilities also include leading the design and development of advanced ML/NLP products from concept through production, including training, optimization, and deployment.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. The engineer will lead the design and development of advanced ML/NLP products from concept through production, including model training, optimization, and deployment.
The Pre-Sales Engineer will act as a technical advisor during early engagement stages, helping clients align technical solutions like AI/ML and LLMs with their strategic business goals. Key duties include leading technical discovery, designing solution architectures (including RAG and vector databases), and creating technical Proofs of Concept (PoCs) to support proposals.
The role involves designing and implementing modern AI-based applications, co-creating efficient solution architectures, and developing clear, maintainable project documentation. Responsibilities also include participating in software deployments and collaborating with users to resolve issues.
The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. The engineer will lead the design and development of advanced ML/NLP products from concept through production, including model training, optimization, and deployment.
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The role involves architecting and building agentic workflows that integrate large language models, reasoning components, and data pipelines to create adaptive conversational systems. The engineer will lead the design and development of advanced ML/NLP products from concept through production, including experimentation with new agentic approaches.
Lead and mentor a team of engineers while driving the architecture and development of AI solutions. Oversee observability systems for the Ad Display platform and ensure high performance at scale.
The role involves integrating Large Language Models (LLMs) and other Generative AI models into web applications through efficient API design and development. Key tasks include building robust Python back-end systems, maintaining data pipelines, and deploying AI applications using containerization technologies.
You will design, implement, and deploy end-to-end NLP and deep learning systems while building LLM-powered applications. You will also be responsible for developing and maintaining production Python services and scaling systems to handle high volumes of requests.
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