WHAT YOU WILL DO ...
As a Staff Machine Learning Engineer in our central Machine Learning Engineering teams within sennAI department you will help us in achieving “Automated & Data-Driven Road Logistics”. You will closely work with our multidisciplinary group of ML&AI engineers, data scientists, backend/frontend engineers and technical product people that are passionate by the new AI-empowered digitalization wave that is changing our world. In this role you will..

- Define the new state-of-the-art for machine learning engineering in the road logistics services

- Apply data science concepts to solve problems like pricing optimization, load-to-carrier recommendation, load search and logistics network optimization, among others

- 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 review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

- 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

- Enforce the best principles in ML System Design by balancing the feedback loop on data exploitation and data acquisition, follow the 80/20 ruling, focus on the right metric in every design decision and once a shippable amount of value is created, go live, evaluate, learn and iterate


WHAT WE ARE LOOKING FOR ...

- Highly motivated with excellent communication and strong interpersonal skills

- 4+ years of experience in deploying and maintaining in production data pipelines working at scale which are fueling and/or being fueled by machine learning models in production

- Above-average Python software engineering skills, including best practices like CI/CD and Git

- 2+ years of experience with modern MLOps setups

- Teamaholic. We don’t believe in super-heroes but rather in super-teams: teams that own products and are the single unit of work :)

- Large experience with Agile philosophies (e.g.: Scrum, Scrumban, Kanban, XP) and project management tools (e.g.: JIRA)

- Consensus building mindset, big picture focus and ability to disagree and commit in order to establish a bias to action by default

- Solid understanding of machine learning product lifecycle and the commonly associated components (MLOps): Experimental Environment (e.g.: Jupyter Notebook, MLflow) Workflow management (e.g.: Air-flow), Feature Stores (e.g.: Feast), DataOps/Pipelines (e.g.: Kafka), Model Deployment (e.g.: Terraform), Testing, Serving (e.g.: Docker, Flask). and Monitoring (e.g.: Datadog), Model Repository (e.g.: DVC)*


WHAT YOU CAN EXPECT:
At sennder, we want to maximize the individual potential of all employees and reinforce an inclusive culture and environment of continuous learning that empowers people to succeed as a team. In addition to humility, we value commitment, team spirit and respect to build fruitful collaboration across teams. Learn more about who we are on

- Fast growth scale-up with an international team of 1000+ people, 74+ nationalities spread across 11 European offices. With English as our common language, we are able to work together.

- Learning and development on the job and with the support of a bi-annual review process, learning allowance, high potential programs, sennder onboarding academy, and internal trainings.