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We are seeking a highly skilled Staff Machine Learning Engineer to join our team at Empresa reconocida. As a key member of our Machine Learning Engineering team, you will play a critical role in shaping the future of our company's logistics services.
Key Responsibilities- Define and Implement Machine Learning Strategies: Develop and implement cutting-edge machine learning solutions to drive business growth and improve operational efficiency.
- Mentor and Guide Junior Engineers: Share your expertise and experience with junior engineers, providing guidance and support to help them grow and develop in their careers.
- Review and Improve Technical Roadmaps: Collaborate with cross-functional teams to review and improve technical roadmaps, ensuring alignment with business objectives.
- Design and Develop Health and Performance Monitoring Tools: Design and develop tools to monitor and improve the health and performance of our machine learning pipelines and services.
- Lead Design Reviews and Technical Discussions: Lead design reviews and technical discussions with peers and stakeholders to ensure the adoption of best practices and cutting-edge technologies.
- Review and Provide Feedback on Code: Review and provide feedback on code developed by other engineers, ensuring adherence to best practices and coding standards.
- Lead Cross-Team Alignment Efforts: Lead cross-team alignment efforts to ensure technical dependencies are identified and addressed, and that artificial intelligence-related topics are properly addressed.
- Highly Motivated and Excellent Communication Skills: Possess excellent communication and interpersonal skills, with the ability to motivate and inspire team members.
- 4+ Years of Experience in Deploying and Maintaining Data Pipelines: Have 4+ years of experience in deploying and maintaining data pipelines that fuel and/or are fueled by machine learning models in production.
- Above-Average Python Software Engineering Skills: Possess above-average Python software engineering skills, including best practices like CI/CD and Git.
- 2+ Years of Experience with Modern MLOps Setups: Have 2+ years of experience with modern MLOps setups.
- Team-Oriented Mindset: Possess a team-oriented mindset, with the ability to work collaboratively with cross-functional teams.
- Large Experience with Agile Philosophies and Project Management Tools: Have large experience with Agile philosophies (e.g., Scrum, Scrumban, Kanban, XP) and project management tools (e.g., JIRA).
- Consensus Building Mindset and Big Picture Focus: Possess a consensus building mindset, with the ability to focus on the big picture and drive results.
- Solid Understanding of Machine Learning Product Lifecycle: Have a solid understanding of the machine learning product lifecycle and the commonly associated components (MLOps): Experimental Environment, Workflow management, Feature Stores, DataOps/Pipelines, Model Deployment, Testing, Serving, and Monitoring.
- Experience with MLOps Stack: Have experience with the following MLOps stack: BentoML for model serving, Weights & Biases for Experimentation Platform, Ray for model training, and Flyte for orchestration of ML Workflows.
- Top-Tier Academic Track on ML Related Conferences: Have a top-tier academic track on ML related conferences (e.g., KDD, NeurIPS, ICML, AAAI, ECML/PKDD).
