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Lead Machine Learning Engineer
hace 2 meses
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 strategies to drive business growth and improve logistics services.
- Mentor and Guide Team Members: Mentor and guide junior to senior engineers, enabling them to deliver successful and impactful software projects.
- Review and Improve Technical Roadmaps: Review and improve technical roadmaps and deliveries across teams to ensure alignment with business objectives.
- Design and Develop Health and Performance Monitoring Tools: Design and develop health and performance monitoring tools for data pipelines and machine learning services in production.
- Lead Design Reviews and Technical Discussions: Lead design reviews and technical discussions with peers and stakeholders to ensure the adoption of best practices and technologies.
- Review and Provide Feedback on Code: Review and provide feedback on code developed by other developers to ensure adherence to best practices and standards.
- Lead Cross-Team Alignment Efforts: Lead cross-team alignment efforts on technical dependency finding and matching, cross-domain architectural design, and artificial intelligence-related topics.
- Enforce Best Principles in ML System Design: Enforce best principles in machine learning system design by balancing the feedback loop on data exploitation and data acquisition, following the 80/20 ruling, and focusing on the right metric in every design decision.
- Highly Motivated and Excellent Communication Skills: Possess highly motivated and excellent communication skills, with the ability to work effectively with cross-functional teams.
- 4+ Years of Experience in Deploying and Maintaining Data Pipelines: Have 4+ years of experience in deploying and maintaining data pipelines working at scale, which are fueling and/or being 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, including experimental environments, workflow management, feature stores, data operations, model deployment, testing, serving, and monitoring.
- Team-Oriented Mindset: Possess a team-oriented mindset, with the ability to work effectively in a collaborative environment.
- 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 and big picture focus, with the ability to disagree and commit to establish a bias to action by default.
- Solid Understanding of Machine Learning Product Lifecycle: Have a solid understanding of machine learning product lifecycle and the commonly associated components (MLOps): experimental environments, workflow management, feature stores, data operations, 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).
At Empresa reconocida, we want to maximize the individual potential of all employees and reinforce an inclusive culture and environment. As a Staff Machine Learning Engineer, you will have the opportunity to work on cutting-edge machine learning projects, collaborate with a talented team of engineers, and contribute to the growth and success of our company.
