Machine Learning Ops Engineer

Posted 3 days agoViewed

💎 Seniority level: Senior, 5+ years

📍 Location: US

🔍 Industry: Software Development

🏢 Company: Weave👥 501-1000💰 $70,000,000 Series D over 5 years agoMedical SaaS VoIP Unified Communications Small and Medium Businesses Software

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: AWSBackend DevelopmentDockerPostgreSQLPythonSQLCloud ComputingData AnalysisGCPGitKubernetesMachine LearningMLFlowAPI testingData engineeringData scienceGoREST APICI/CDDevOpsMicroservicesData visualizationData modeling

Requirements:

5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).
Experience moving and storing TBs of data or 100M’s to 10B’s of records.
Demonstrated experience with common MLOps technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
Experience with data labelling or annotation for audio or NLP use cases.
Understanding of distributed systems and building scalable, redundant, and observable services.
Expertise in designing and architecting systems for distributed data sets and services
Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
Experience providing stable well designed libraries and SDKs for internal use.
Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.

Responsibilities:

Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.
Help product and development teams understand the data lifecycle and the inherent 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 help them understand common patterns, anti-patterns, and tradeoffs of machine learning. 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 code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.
Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.
Work in a cloud environment, considering the implementation of functionality through several distributed components and services.
Work with our stakeholders to translate product goals into actionable engineering plans.

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