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Senior Machine Learning Engineer Position
hace 2 meses
We are seeking a highly skilled Staff Machine Learning Engineer to join our central Machine Learning Engineering teams within the sennAI department at Sennder.
As a Staff Machine Learning Engineer, you will play a key role in achieving Automated Data-Driven Road Logistics by helping us define the new state-of-the-art for machine learning engineering in the road logistics services.
Key Responsibilities- Define Machine Learning Engineering Standards: Develop and maintain the technical roadmap for machine learning engineering in the road logistics services.
- Apply Data Science Concepts: Utilize data science concepts to solve complex problems such as pricing optimization, load-to-carrier recommendation, load search, and logistics network optimization.
- Mentor and Review: Mentor junior to senior engineers, enabling them to deliver successful impactful software projects, and review technical roadmaps and deliveries across teams.
- Design and Develop MLOps Tools: Design and develop health and performance monitoring tools for data pipelines and machine learning services in production.
- Lead Design Reviews: Lead design reviews with peers and stakeholders to decide on available technologies and ensure best practices.
- Code Review and Feedback: Provide feedback to ensure best practices, such as style guidelines, code accuracy, testability, and efficiency, while reviewing code developed by other developers.
- Technical Alignment: Lead the cross-team alignment effort on technical dependency finding and matching cross-domain architectural design and Artificial Intelligence related topics.
- ML System Design: Enforce the best principles in ML System Design by balancing the feedback loop on data exploitation and data acquisition, following the 80/20 ruling, focusing on the right metric in every design decision, and evaluating, learning, and iterating once a shippable amount of value is created.
We are looking for a highly motivated individual with excellent communication and strong interpersonal skills.
Key requirements include:
- 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.
- Team-oriented.
- 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. 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).
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.
We value commitment, team spirit, and respect to build fruitful collaboration across teams.
Learn more about who we are on our website.
