Staff Machine Learning Engineer
Location: Multi-Location (2 Locations) · Category: Data, AI & Analytics · Seniority: Lead · Posted: April 21, 2022 · Verified: Oct 10, 2026
Role Overview & Description
Track team expansion and market signals for Hive
Polaris7 monitors open roles, strategic market movements, and M&A developments in real time. Get automated intelligence briefings on Hive and benchmark against direct competitors.
Hive
thehive.aiEnterprise AI APIs for moderation, fraud detection and content safety.
Unlock full company profile, competitors & live market signals for Hive
Similar Positions in DACH
Related roles across advertising, media, and data
This staff-level role leads the development and deployment of machine learning models at scale, architecting ML pipelines and optimizing model performance. It also involves mentoring junior engineers to advance AI capabilities.
This Staff Machine Learning Engineer role on the ML Efficiency team builds infrastructure and tooling to optimize ML training and inference at scale. The engineer will improve GPU utilization, develop benchmarking frameworks, and drive technical strategy for platform scalability and cost efficiency. Requires 5+ years of software engineering experience with strong Python and distributed systems expertise.
Leads a team of machine learning engineers to design, build, and deploy ML models and pipelines. Ensures technical excellence, mentors team members, and collaborates with product and engineering to deliver AI solutions.
Madhive is the leading independent and fully customizable operating system built to help local media professionals build profitable, differentiated, and efficient businesses. Madhive empowers sales teams to extend their reach into streaming and connects local advertisers with the communities they se
More Positions at Hive
3 more open roles
This role supports the Hive Models team in defining product requirements and implementation, collaborating with ML, Core Infrastructure, and Product teams. The APM will contribute to the development of cloud-hosted deep learning models and build a foundation for future product ownership.
This role supports the Data Operations team in developing proprietary AI models by managing projects that deliver high-quality training and testing datasets. The analyst will analyze priorities, metrics, and deliverables, playing an essential part in the product development lifecycle within a fast-growing startup.
This role involves working directly with customers to deploy and customize Hive's AI solutions, often integrating them into client environments. The engineer will build and adapt software to meet specific customer needs, requiring strong problem-solving and communication skills.