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LeadFull-timePythonAWSGCPKubernetesMachine LearningData ScienceAgileGitAIML
Salary Range
$30,600 - $41,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
Weave is seeking a Machine Learning Engineer to join their self-empowered teams and contribute to making machine learning more approachable and data more available. You will be part of a team focused on building AI-powered features and enabling product innovation through scalable machine learning solutions.
Key Responsibilities
- →Design and develop machine learning infrastructure, tooling, and models to deliver world-class experiences.
- →Help product and development teams understand the data lifecycle and the experimental nature of machine learning.
- →Build internal products and platforms to enable teams to incorporate AI into their features and customer-facing products.
- →Consult with teams to guide them through creating excellent customer experiences end-to-end.
- →Build scalable, resilient services to support data integration, event processing, and platform extensions.
- →Contribute to the continued evolution of product functionality that services large amounts of data and traffic.
- →Write high-quality, performant, sustainable, and testable code.
- →Coach and collaborate with others, sharing expertise and encouraging best practices.
- →Work in a cloud environment, implementing functionality through distributed components and services.
- →Translate product goals into actionable engineering plans.
Requirements
- ✓8+ years of experience in Machine Learning or AI, preferably with a focus on natural language.
- ✓Experience moving and storing TBs of data or 100M’s to 10B’s of records.
- ✓Experience building and deploying ML-driven B2B multi-tenant applications in production environments at scale.
- ✓Experience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
- ✓Understanding of distributed systems and building scalable, redundant, and observable services.
- ✓Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
- ✓Demonstrated track record of delivering complex projects on time and experience working in enterprise-grade production environments.
- ✓Demonstrated leadership experience leading large projects or teams.
- ✓Strategic thinker with a strong technical aptitude and a passion for execution.
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