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Machine Learning Engineer
hace 2 meses
We are revolutionizing the way of doing business at a global scale with Machine Learning (ML) and Artificial Intelligence (AI). Sennder is a European digital freight forwarder with a data-centric approach to build the next generation of supply chain and road logistics services.
We are looking for a Staff Machine Learning Engineer to join our central Machine Learning Engineering teams as part of the sennAI department. The department's mission is to achieve "Automated & Data-Driven Road Logistics." Our team is a large, diverse, and multidisciplinary group of ML & AI engineers, data scientists, backend/frontend engineers, and technical product people passionate about the new AI-empowered digitalization wave.
sennAI's purpose is to build proprietary technology that can automate sales, brokerage, and other business-related activities. Such automation can enable a flywheel where data acquisition and revenues grow exponentially with one another. Our teams create best-in-class predictive analytics services while approaching ML Engineering in a holistic, end-to-end fashion: from best practices in ML modeling to engineering excellence around our MLOps Platform.
Every day, we acquire 3M+ new real-time data points about the road logistics industry in Europe. This data is used to build the future of logistics marketplaces where pricing optimization, load-to-carrier recommendation, load search, and network optimization happen in an automated fashion.
KEY RESPONSIBILITIES:- Define the new state-of-the-art for machine learning engineering in road logistics services.
- Apply data science concepts to solve problems like pricing optimization, load-to-carrier recommendation, load search, and logistics network optimization.
- Mentor junior to senior engineers, enabling them towards successful & impactful software deliveries.
- Review technical roadmaps and deliveries across teams.
- Design and develop health and performance monitoring tools (MLOps) of data pipelines and the machine learning services in production.
- Lead design reviews with peers and stakeholders to decide amongst available technologies.
- Be hands-on when needed while reviewing code developed by other developers and providing feedback to ensure best practices.
- Lead the cross-team alignment effort on technical dependency finding and/or matching, cross-domain architectural design, and all-in-all Artificial Intelligence related topics.
