Top Machine Learning Jobs in Romania

Lead Data Scientist responsible for managing data science projects, integrating advanced modeling techniques, collaborating with stakeholders, and ensuring data quality while driving measurable business outcomes.

Lead data science projects, integrating statistical expertise with business needs, collaborating with stakeholders, and ensuring ethical AI practices. Responsibilities include designing experiments, implementing models, and coaching team members.

Lead the development and enhancement of LLM-powered products, collaborating with cross-functional teams to create innovative AI-driven solutions.

The role involves building and iterating machine learning models, collaborating with stakeholders to address Trust & Safety issues, deploying models in production, and improving team performance through knowledge sharing and documentation.

Seeking a seasoned data scientist to advance methodologies for cardiovascular health assessment, collaborating with medical experts and algorithmic team.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

The ML Research Engineer will develop and deploy computer vision algorithms, mentor junior engineers, and collaborate across teams to enhance item authentication solutions.

The role involves deploying and maintaining machine learning pipelines, developing retrieval-augmented generation systems, and optimizing model performance, requiring extensive experience in ML Ops and software engineering.

As a Senior Cloud Architect, you will architect, deploy and manage AI/ML cloud solutions while mentoring team members and optimizing workflows.

As a Senior Cloud Architect, you will architect, deploy, and manage cloud-based AI/ML solutions, leveraging AWS technologies and providing consultative support to clients.

The Senior Cloud Architect will leverage cloud technologies to address customer needs, focusing on AI/ML solutions while mentoring team members and enhancing personal brand through thought leadership.

Design and implement machine learning models for Generative AI, Computer Vision, and Graphics, impacting digital storytelling and content creation.

The role involves developing data architectures, building Big Data and Lakehouse solutions, and optimizing data processing at scale. Responsibilities include guiding architecture, engaging in agile development, and promoting software engineering best practices.

Lead a team developing AI solutions focusing on computer vision and generative AI, integrating ML into production workflows, and ensuring ethical practices.

Design, implement, and optimize machine learning platforms; mentor junior engineers and work with global teams on technical design and architecture.

The Lead Applied Machine Learning Engineer will deliver AI/ML solutions, coordinate projects, and build scalable data products to solve business challenges.

The Machine Learning Engineer will develop and deploy ML solutions, collaborate with teams, engage with customers, and promote achievements.

Lead the AI/ML team to develop innovative solutions for environmental challenges, emphasizing strategic guidance, collaboration, and team empowerment.

The Senior ML Engineer will enhance fine-tuning methodologies, research inference optimization techniques, and re-implement LLM architectures focusing on distributed training and efficiency.

As an ML Ops Engineer, you will manage AWS-based ML infrastructure, streamline model deployment and CI/CD pipelines, and ensure reliable, production-ready models through monitoring and observability practices.

Research and implement physics-informed AI algorithms and workflows, supervise teams, publish research, and collaborate for Autodesk's design and engineering tools.

Design and implement advanced LLM applications for payroll, lead architecture and optimization efforts, collaborating with diverse teams and enhancing system reliability.

Responsible for developing AI/ML solutions in cloud-based environments, optimizing pipelines, integrating ML models, and mentoring junior staff.

Develop and optimize customer-focused AI-driven cloud services, strategies and integrate ML/AI models onto platforms while ensuring high performance and effective operations.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.