Top Machine Learning Jobs in Bucharest

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

The Innovation Labs Expert will drive technical innovation, prototype multi-vendor solutions, and collaborate with sales teams to deliver proof-of-concepts for advanced wireless architectures.

The Pricing Actuary will develop pricing tools, support account pricing, conduct analyses, and contribute to regulatory tasks while collaborating with underwriters.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

As an AI Operations & Automation Specialist, you will optimize finance and HR operations through automation, AI implementation, and process improvement while ensuring data integrity and supporting various teams in the company.

As a Senior Product Data Analyst, you'll influence product and marketing strategy using data; analyze customer behavior, build dashboards, and partner across teams to drive data-driven decisions.

Lead the LLM team in architecting, deploying, and managing AI models that enhance user interactions. Involve in coding, mentoring, and improving moderation systems for an AI companion platform.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

The Principal Data Product Manager will lead ML and AI initiatives, define strategies, manage product roadmaps, and collaborate with teams to deliver scalable solutions that drive business outcomes.

The Senior Data Analytics Engineer will design and maintain analytical pipelines, write SQL for large datasets, utilize AI tools, and communicate insights to stakeholders.

As an AI Research Engineer, develop reinforcement learning algorithms, optimize decision-making, debug and enhance learning pipelines, and integrate models into production systems.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

Define strategy and roadmap for analytics and predictive intelligence for MSPs. Engage partners and users, translate insights into PRDs, prioritize backlogs, and ship AI-powered analytics. Lead market analysis, GTM, beta programs, and measure adoption, detection accuracy, and business impact.

Develop and modernize Ubisoft's internal crash reporting system across multiple components. Revamp C# desktop/web UIs, design REST APIs, integrate telemetry and AI assistance, collaborate with production and engine teams to improve UX and tooling efficiency.

As a Senior Product Manager, you will define product vision, analyze market trends, manage product KPIs, and collaborate with teams to deliver innovative solutions.

The role involves reviewing AI-generated outputs, analyzing multimedia, and providing culturally relevant content feedback. Strong analytical skills and attention to detail are required.

Develop and maintain applications using Python, focusing on integrating AI and machine learning, implementing ETL processes, and optimizing applications for performance and scalability.

Design and implement AI/ML and computer vision solutions on Microsoft Azure, focusing on scalable, production-ready systems. Responsibilities include mentoring, ensuring performance, and guiding best practices.

The Senior Product Manager will own and drive the development of Kraken's Algorithmic Execution & Strategy Engine, focusing on execution algorithms, API specifications, and client engagement to optimize trading strategies.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The role involves building, training, and deploying machine learning models using AWS tools, optimizing workloads, and collaborating with data engineers.

The role involves developing and deploying big data anti-fraud detection solutions using Python and PySpark while collaborating with team members to ensure quality code and production support.

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

Design and build simulation environments for robotics research, implement RL algorithms, and evaluate policies for stability and transfer potential. Collaborate with teams and document results.

The Machine Learning Engineer develops and deploys NLP and generative AI models, integrating them with business applications and ensuring code quality.