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ManagerFull-timePythonJavaC#AWSGCPKubernetesPostgreSQLRedisMachine LearningData Science
Salary Range
$163,200 - $220,800 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
Weave is seeking an Engineering Manager to lead a team of machine learning engineers. This role involves providing technical leadership, guiding the team through rapid software development, and ensuring the delivery of impactful solutions. The ideal candidate will foster the technical and professional growth of team members.
Key Responsibilities
- →Lead and mentor a team of machine learning engineers, providing career coaching and support
- →Foster a customer-centric mindset within the team
- →Collaborate with other teams to define technical roadmaps and manage cross-functional initiatives
- →Communicate effectively with stakeholders, distilling complex situations into actionable plans
- →Drive the development process and best practices, focusing on delivering incremental customer value
- →Provide clear, actionable project and development advice to your organization
- →Ensure the development of scalable and redundant services using distributed systems and web-scale infrastructure
- →Demonstrate expertise in Go or Python Programming Language and distributed systems
- →Demonstrate expertise in Machine Learning and Gen AI skillsets and operations
Requirements
- ✓Bachelor's degree in Computer Science or related technical field, or equivalent practical experience
- ✓6+ years of engineering or related experience, including technical and organizational leadership
- ✓Strong understanding of distributed systems and experience in building scalable and redundant services
- ✓Experience with data and analytical systems such as PostgreSQL, data warehousing, data lakes, embedded analytics, or similar technologies
- ✓Operational experience with web-scale infrastructure on public cloud deployments (GCP, AWS, Kubernetes)
- ✓Solid understanding of a backend language (Go, Python, Java, C#, etc.)
- ✓Solid understanding of data science, machine learning models, operations and deployment methodologies
