Top Artificial Intelligence Jobs in Romania

Join Welo Data’s Nepali contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s contributor network for flexible, remote AI projects involving text, image, or audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Candidates need native or near-native Kannada fluency, English proficiency, digital tool comfort, and strong attention to detail. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s Vietnamese AI contributor network for potential remote projects involving text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Projects vary in duration and compensation, with details provided before participation.

Join a remote global contributor network supporting AI data projects. Depending on project needs, you may annotate content, evaluate search results or chatbot responses, create prompts, and verify cultural and linguistic accuracy. Projects range from a few days to several weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s global contributor network for flexible, remote AI projects involving text, image, and audio annotation; search, advertisement, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Hebrew, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s Cantonese AI Trainers Network to support AI data annotation, evaluation, and prompt creation. Work remotely with flexible hours while contributing language and cultural expertise to improve AI systems. Applicants should be native or near-native Cantonese speakers living in Hong Kong, Macau, mainland China, or Malaysia, with strong English skills, digital tool proficiency, attention to detail, and curiosity.

Operates and integrates AI systems including RAG pipelines, copilots, agentic workflows, and predictive ML services. Designs observability frameworks, monitors model quality, usage, reliability, latency, and costs, and supports incident resolution and post-mortems. Optimizes AI workloads through model selection, caching, and orchestration while defining SLAs and SLOs. Collaborates with engineering, product, and business stakeholders to troubleshoot production systems and communicate technical issues clearly.

Own HR support across recruitment sourcing, employee and manager advisory, HR projects, talent reviews, reorganizations, and process improvement. The role partners with stakeholders, supports global HR, advises on performance and policy matters, and develops AI-enabled HR processes and automation. It requires independent execution, strong stakeholder management, broad hands-on HR experience, and comfort managing varied priorities in a remote, cross-border environment.

Develop and enhance MetaMask social and multi-chain experiences across Portfolio, browser extension, and mobile platforms. Collaborate across teams on complex projects, mentor engineers, and build scalable full-stack applications using React, React Native, modern JavaScript, blockchain technologies, APIs, testing, and continuous integration. Ensure cross-platform compatibility and apply web security best practices.

Design AI-powered party, social, and multiplayer game mechanics using LLMs and conversational AI characters. Collaborate with artists and programmers, iterate through playtests, pitch new features, and refine gameplay for major game projects. The role requires strong communication, teamwork, adaptability, and the ability to meet deadlines in creative, fast-paced environments.

Lead the architecture and production delivery of AI agents and intelligence systems for payments. Build reliable, low-latency LLM applications with tool use, orchestration, memory, RAG, multilingual conversations, evaluation, observability, and safety guardrails. Develop merchant intelligence and AI operations automation, mentor engineers, establish technical direction, and collaborate across Product, Data Science, and engineering teams in a compliance-sensitive global environment.

Build and maintain production-grade agentic AI systems for an internal AI platform. Design AWS infrastructure, knowledge graph solutions using Neptune or Neo4j, and LLM-based reasoning and retrieval workflows. Troubleshoot integrated systems, collaborate across teams, influence technical direction, and support engineering best practices. The contract is expected to last 4–6 months, with possible extension, and requires strong Python, AWS platform engineering, and agentic AI expertise.

Develop, deploy, and maintain scalable AI/ML pipelines and production models, including LLMs and generative AI. Optimize model performance, latency, and cost across AWS, GCP, and Azure. Apply MLOps practices such as CI/CD, versioning, monitoring, logging, and maintenance. Collaborate with data scientists, software engineers, solution architects, and cross-functional teams to integrate AI capabilities into products and workflows.

Open unsolicited applications for IT professionals across software development, DevOps, cloud, data migration, ECM, QA, AI, data analysis, project management, and IT operations. Join the talent pool to be considered for future roles; strong communication, technical background, problem-solving, teamwork, and growth mindset expected.

Lead KPI analysis to drive business performance, identify gaps and implement improvements, support strategic decisions with data insights, work with leadership across locations, propose digital and AI solutions, and travel to commercial sites to implement initiatives.

Design difficult open-web research problems for benchmarking frontier AI browsing agents. Responsibilities include constructing multi-step questions, validating clues across databases, archives, registries, and PDFs, documenting auditable evidence trails, recording search validation results, testing research difficulty, resolving ambiguity, and delivering reproducible research documentation.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Build and deploy production-grade LLM capabilities for the Kayzen Console. Responsibilities include developing AI-backed APIs and full-stack features, implementing RAG, embeddings, agents, and tool calling, and establishing evaluation, monitoring, observability, and feedback systems. The role optimizes quality, latency, reliability, and cost; troubleshoots production issues; collaborates with Product, ML, and Engineering; and turns prototypes into maintainable AI products.

Leads global privacy and AI legal matters for a SaaS employment platform. Advises Product, Engineering, Security, and business teams on privacy by design, AI governance, data protection, workforce data, incidents, regulatory compliance, vendor reviews, transfers, and contract terms. Builds scalable policies, controls, templates, training, and customer-facing trust materials while monitoring global privacy and AI regulations.

Design and implement AI/ML compiler technologies for embedded ARM and RISC-V hardware using C++ and LLVM. Develop MLIR and graph compiler features, optimize model lowering, fusion, tiling, scheduling, code generation, and inference performance. Collaborate with hardware architects, ML researchers, and global development teams to support automotive system-on-chip platforms. Analyze generated code with simulators and profilers while contributing to open-source compiler technologies.

Develop AI/ML compiler technologies for embedded ARM and RISC-V processors, optimizing models through graph compilation, lowering, fusion, tiling, scheduling, code generation, and performance analysis. The role involves C++ and LLVM/MLIR development, collaboration with hardware architects and ML researchers, compiler support for automotive SoCs, and contribution to open-source projects.

Design and implement AI/ML compiler technologies for embedded ARM and RISC-V processors using C++, LLVM, and MLIR. Optimize machine learning models through graph-level transformations, lowering, fusion, tiling, scheduling, code generation, and performance analysis. Collaborate with hardware architects, ML researchers, compiler consumers, and global development teams to deliver production compiler features for automotive SoCs.

Design and implement AI/ML compiler technologies for embedded ARM and RISC-V processors using C++, Python, LLVM, and MLIR. Optimize machine learning models through graph-level transformations, lowering, fusion, tiling, scheduling, and code generation for automotive SoCs. Collaborate with hardware architects, ML researchers, compiler consumers, and global development teams to improve inference performance and compiler quality.

Develop AI/ML compiler technologies for embedded hardware using C++ and LLVM, optimizing models for high-performance inference across semiconductor platforms. Build compiler features for ARM and RISC-V processors, including graph optimizations, model lowering, code generation, and optimization pipelines. Collaborate with architecture teams, internal tool users, and global development teams throughout design, development, and deployment.

Design and implement AI/ML compiler technologies for embedded ARM and RISC-V processors. Develop LLVM and MLIR compiler features, optimize graph-level workloads through lowering, fusion, tiling, and scheduling, and improve code generation performance across semiconductor platforms. Collaborate with hardware architects, ML researchers, compiler consumers, and global development teams. Analyze generated code using simulators and profilers while contributing production-quality C++ and Python code to compiler frameworks.