management

sennder

<div>Machine Learning (ML) and Artificial Intelligence(AI) are revolutionizing the way of doing business at a global scale. sennder is a European digital freight forwarder with a data-centric problem-solving approach to build the next generation of supply chain and road logistics services. Do you want to help us to shape the future? We are looking for an Engineering Manager - Machine Learning to join our central ML Recommendations team - as part of sennAI department. The department’s mission is to achieve “Automated &amp; Data-Driven Road Logistics”. We’re a large, diverse and multidiscplinary group of ML&amp;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. We want to attract, retain and grow world-class talent to form a incredible group that can provide you the most productive and growth-friendly time of your career. sennAI purpose is to build proprietary technology that can automate sales, brokerage and other businessrelated activities. Such automation can enable a flywheel where data acquisition and revenues grow exponentially with one another. The scope of our teams is creating best-in-class predictive analytics services while approaching ML Engineering in an holistic, end-to-end fashion: from best practices in ML modelling until engineering excellence around our MLOps Platform that lifts the developer experience to a different realm. Every day, we acquire 3M+ new real-time data points (augmenting by the day!) 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. Can you even imagine where we can go with your help? Let’s #keepOnTrucking... together! YOUR MISSION: <ul> <li>As a people manager: Hire, onboard, manage, engage (including by organising team building events), coach, grow and retain exceptional talent in the areas of machine learning, data science and MLOps; </li> <li>As a leader: foster an environment of trust, self-organization, empowerment, Agile-first mindset, failurefriendly but mandatory-learnings towards to both personal and professional growth; </li> <li>As a individual contributor, you will hands-on address some of the following challenges (whenever time allows and promoting a culture of leading by example): <ul> <li>Define the new state-of-the-art for machine learning engineering in the road logistics services;</li> <li>Prototype and subsequently operationalize innovative, data-intensive, end-to-end machine-learning-based decision engines, following the latest best practices on MLOps;</li> <li>Outline and develop health and performance monitoring tools (MLOps) of data pipelines and the machine learning services in production; 1/2</li> <li>Design and improve heterogeneous, asynchronous and high-performance large-data processing pipelines from/to multiple sources/destinations;</li> <li>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;</li> </ul> </li> </ul> YOUR PROFILE: <ul> <li>Highly motivated with excellent communication and strong interpersonal skills;</li> <li>Proven experience in people management (onboarding, offboarding, individual development plans, performance review &amp; management, hiring/letting go, 1-on-1s, continuous feedback, organizing team building events) in the tech industry (2+ yrs.);</li> <li>Proven experience in hands-on contribution to machine learning engineering teams in the tech industry (2+ yrs.);</li> <li>M.Sc or PhD in a quantitative field and/or working experience as a Data Scientist, Machine Learning Engineer or Data Engineer (MLOps);</li> <li>Teamaholic. We don’t believe in super-heroes but rather in super-teams: teams that own products and are a single unit of work :)</li> <li>Experience with working on Machine Learning projects to learn from structured data, as well as, deep knowledge on statistics;</li> <li>Solid Python and software engineering skills, including best practices like CI/CD and Git;</li> <li>Experience with Agile philosophies (e.g.: Scrum, Scrumban, Kanban, XP) and project management tools (e.g.: JIRA);</li> <li>Basic understanding of machine learning product lifecycle and the commonly associated components (MLOps): Experimental Environment (e.g.: Jupyter Notebook, MLflow) Workflow management (e.g.: Airflow), 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) *</li> <li>Fluent written and verbal communication in English;</li> </ul> BONUS: <ul> <li>Deep knowledge of the theory and expertise on the application of Machine Learning;</li> <li>PhD in Machine Learning and/or data mining fundamental topics and/or non-trivial applications of ML/DM foundations AND/OR Top tier academic track on ML/DM conferences (e.g.: KDD, NeurIPS, ICML, AAAI, ECML/PKDD);</li> <li>Experience on MLOps in modern cloud systems (preferentially, AWS);</li> <li>Experience in managing remote and geographically distributed teams;</li> </ul> * List of technologies/methodologies is for illustrative purposes. You are not expected to have experience in each single one of these technologies/methodologies. 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 <a href="https://www.sennder.com/career">our career site.</a> <ul> <li>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.</li> <li>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.</li> <li>Various opportunities to connect with colleagues through regular team events and company get-togethers such as our highly anticipated sennder <a href="https://www.youtube.com/watch?v=vJ9clvLImHE&amp;t=89s">Summer Camp</a>.</li> <li>Prioritize employee engagement and mental well-being by fostering a supportive environment through the Likeminded platform and conducting regular employee satisfaction surveys.</li> <li>Flex work model where you seamlessly merge virtual productivity and in-office collaboration with your colleagues.</li> <li>Commuter allowance to assist employees with their daily travel expenses and a one-time home office benefit to ensure that you're properly equipped wherever you work.</li> <li>Competitive compensation package including objective-based bonus, referral reward, and in some cases virtual option plan.</li> <li>Vibrant offices complete with healthy snacks, focus zones, and social areas to connect with your colleagues. Click <a href="https://youtu.be/Ll2LsfpoAzQ?si=Zwf1N6N1XFtVZdve">here</a> for a virtual tour and better yet, hope to see you soon!</li> </ul> We value humility and we're as interested in your character as we are in your talent. Please apply, even if you feel you only meet part of our listed criteria. Diversity drives our innovation and we offer a collaborative, dynamic, and international work environment. Just be yourself. We are excited to meet you and for you to join us in shaping the future of the logistics industry in Europe. If you have any questions or need special accommodation please reach out to us at <a href="mailto:ta@sennder.com">ta@sennder.com</a>. As soon as you apply your journey with sennder begins. #LI-MS1</div>

Engineering Manager - Machine Learning

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