Senior Machine Learning Engineer, Gen AI

Job not on LinkedIn

🕒 April 3

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Weave

WebsiteLinkedInAll Job Openings

1 - 10 employees

Weave is building a generative AI platform and knowledge graph that will revolutionize how life science companies collaborate

📋 Description

• 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.

🎯 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. • Experience building and deploying ML driven B2B multi-tenant applications in production environments. • Experience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others. • Experience with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine Tuning, multi-modal models, and others. • Experience with data labelling or annotation for audio or text 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. • Self driven and a thirst for learning in a quickly changing industry. • Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments. • Strategic thinker with a strong technical aptitude and a passion for execution.

🏖️ Benefits

• Health insurance • 401(k) matching • Remote work options