Top Machine Learning Jobs in Romania

Lead applied AI research and architecture for GenAI in cybersecurity: design LLM architectures, implement production-grade deep learning systems at scale, mentor scientists, set technical standards, and align AI strategy with business goals.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

Perform malware and threat research across the attack lifecycle, validate and improve Falcon detections, collaborate with engineering and ML teams, automate analysis, support external security testing, and translate findings into product protections.

Engineer automation, tooling, and detections to improve incident response operations. Automate workflows, build detections and integrations, develop cloud-native tooling, and collaborate with threat intelligence to speed investigations and reduce false positives.

Provide second-level operations support for core and telco cloud infrastructure: manage incidents, preventive maintenance, ticket lifecycle, performance and lifecycle management, automation scripting, procedures, team coordination and training. Role includes project support, reporting insights, and a six-month deployment to Saudi Arabia.

Work with the Optimization team to build Power Apps solutions, develop Python-based machine learning tools, apply AI tools, document technical workflows, and collaborate on process optimization projects under mentorship.

Support the Optimization Team by building Power Apps solutions, developing Python-based machine learning tools, applying AI tools (e.g., Microsoft Copilot, Amazon Quick) to optimization tasks, documenting workflows, and collaborating on automation and data-dashboard projects.

Support standard operational pricing tasks including data management and loss modelling, assist R&D and P&M process improvements, develop and test pricing tools, produce dashboards and analyses, collaborate with nearshore/onshore teams and IT to expand analytical capabilities.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

Lead cloud application architecture and migration strategy for large-scale Azure programs. Define architecture principles, govern design, drive cloud migration roadmaps, mentor teams, evaluate technologies and vendors, and ensure agile, secure, scalable microservices and data solutions with minimal business disruption.

Drive product adoption and customer outcomes via 1:1 and 1:many channels. Onboard and support scale customers, manage escalations, monitor health indicators, collaborate cross-functionally, run webinars and calls, prioritize high-volume tasks, and help mitigate churn while identifying expansion opportunities.

Serve as primary client contact for multiple accounts, manage and train annotation teams, ensure timely delivery and quality, monitor metrics, resolve issues, and drive process improvements and automation.

Design and maintain enterprise IT and data architecture focused on data governance, MDM, metadata/catalog, and data quality. Lead technical design, implement MDM and metadata solutions, enable AI-driven automation, collaborate with stakeholders, mentor architects, and recommend technologies to improve data discoverability, reliability, and business value.

Support design, maintenance, and operation of SCOR's AI governance framework, ensuring regulatory readiness (EU AI Act), risk management, standards, playbooks, and oversight of internal and client AI solutions. Collaborate with legal, compliance, risk, data, and technology teams to embed ethical, secure, and pragmatic AI guardrails, assess AI risks (bias, explainability, robustness), and promote governance-by-design and enablement across the organization.

Lead design and development of scalable front-end applications using React and TypeScript for an AI/ML-powered cloud-native SaaS platform. Collaborate with product, UX, backend, and ML teams to integrate APIs and real-time services, drive front-end architecture, optimize performance and accessibility, and contribute to testing and continuous improvement.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

Design and build state-of-the-art web applications using Java/Kotlin and Spring Boot. Follow agile, TDD and clean-code practices, mentor peers, work with clients, and contribute to projects including ML cloud detection, public portals, and consumer apps.

Lead and mentor functional safety engineers to define, analyze, and validate ASIL safety requirements for automotive domain controllers, displays, and connectivity. Perform safety analyses (HARA, FTA, FMEDA, FMEA, STPA), align safety with cybersecurity and ML considerations, coordinate verification/validation activities, and integrate safety concepts with development partners and suppliers.

Lead the product vision, roadmap, and backlog for AI-powered HR and workforce management SaaS solutions. Collaborate with stakeholders, engineering, AI specialists and UX to define, prioritize, and deliver generative AI, conversational AI, and automation features; validate hypotheses, define success metrics, ensure secure and auditable AI integrations via APIs, and act as the customer advocate balancing business value and technical feasibility.

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.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Design, develop, and maintain data pipelines and large-scale processing systems to ensure data accessibility, reliability, and efficient processing. Build ETL/ELT flows, integrate multiple data sources, support data warehousing and reporting, implement APIs and orchestration, optimize data architectures, and apply algorithmic/statistical methods (including AI) to enable analysis and downstream consumption.

Lead global marketing strategy and GTM to scale Aisle into a market leader. Own brand, PR, product positioning, full-funnel demand generation, ABM, marketing tech stack, RevOps, attribution, budget/agency management, and grow a multidisciplinary marketing team aligned to revenue targets.