Weave is the all-in-one experience platform for small- and medium-sized healthcare businesses. From the first phone call to the final invoice and every touchpoint in between, Weave connects the…
Weave is the all-in-one experience platform for small- and medium-sized healthcare businesses. From the first phone call to the final invoice and every touchpoint in between, Weave connects the…
What they do: All‑in‑one communications and engagement platform for small/medium healthcare and SMB practices (phone/VoIP, texting, payments, scheduling, reviews, AI features)
HQ: Lehi, Utah
Founded by: Brandon Rodman, Jared Rodman, Clint Berry
Notable funding: $70M Series D led by Tiger Global (Oct 2019); earlier $5M Series A (2014)
Employee count (sample): 1143
Company Overview
Problem Domain
Customer communications and practice management for small/medium healthcare and local businesses.
Industry
Software Development
Funding Track Record
Series A- June 2014
$5M
Reported Series A reported in June 2014
Series C- December 2018
$37.5M
Growth round led by Lead Edge Capital with participation from existing investors
Series D- October 2019
$70M
Series D led by Tiger Global with participation from Bessemer, Catalyst, Crosslink, Pelion and Lead Edge
Investor Signal
“Backed by growth and venture investors including Tiger Global Management, Bessemer Venture Partners, Catalyst Investors, Crosslink Capital, Lead Edge Capital and Pelion Venture Partners”
Founders
What we do
Join the Team
ML Engineer - Gen AI
RemoteUS
Remote • US
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About The Company
Weave is a forward-thinking technology company dedicated to transforming the way businesses and consumers connect through innovative solutions. Our mission is to empower organizations with cutting-edge tools that enhance communication, streamline operations, and foster meaningful customer relationships. With a focus on leveraging artificial intelligence and scalable backend systems, Weave strives to create seamless, intelligent experiences that drive growth and efficiency. Our culture emphasizes collaboration, continuous learning, and a passion for solving complex challenges, making us a dynamic place for talented professionals to thrive and make a tangible impact in the industry.
About The Role
Weave is seeking an experienced Machine Learning Engineer to join our innovative team. In this role, you will be at the forefront of developing scalable machine learning infrastructure, models, and tooling that enable our product teams to deliver AI-powered features. You will work closely with cross-functional teams comprising product owners, backend and frontend developers, and DevOps engineers to build resilient services that handle large-scale data processing and AI integration. Your work will directly impact how our customers experience Weave’s platform, making advanced AI functionalities accessible, reliable, and user-friendly. This position offers the flexibility of remote work within the US, with the option to work onsite at our Lehi, UT headquarters if preferred. Reporting directly to the Engineering Director, you will play a pivotal role in shaping the future of AI-powered solutions at Weave.
Qualifications
Responsibilities
Design, develop, and maintain machine learning infrastructure, tools, and models to support product innovation and customer experience enhancements.
Benefits
Competitive salary and comprehensive health benefits package.
Flexible remote work options within the US, with potential for onsite collaboration at our Lehi, UT headquarters.
Opportunities for professional development and continuous learning through conferences, training, and certifications.
Inclusive and collaborative company culture that values diversity and innovation.
Access to cutting-edge AI tools and resources to support your work and growth.
Generous paid time off and work-life balance initiatives.
Participation in company-wide initiatives and events fostering community and engagement.
Equal Opportunity
Weave is an equal opportunity employer committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome applicants of all backgrounds, regardless of race, color, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or any other legally protected characteristics.
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8+ years of professional experience in Machine Learning or Artificial Intelligence, with a focus on natural language processing (NLP).
Proven experience handling and processing large datasets, ranging from hundreds of millions to billions of records.
Extensive experience building and deploying ML-driven B2B multi-tenant applications in production environments at scale.
Proficiency in programming languages such as Python, and familiarity with tools like Jupyter, MLFlow, KubeFlow, DVC, Triton Server, and Postgres.
Hands-on experience with modern ML techniques including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, Fine Tuning, and multi-modal models.
Knowledge of data labeling and annotation processes for audio and text datasets.
Strong understanding of distributed systems architecture, building scalable, redundant, and observable services.
Experience working in cloud environments such as AWS or GCP, with capabilities in deploying and managing distributed components.
Demonstrated ability to develop stable, well-designed libraries and SDKs for internal use.
Excellent collaboration skills, with a history of leading large projects and working effectively across multiple teams and stakeholders.
Self-motivated with a continuous learning mindset, eager to stay current with emerging AI technologies.
Proven track record of delivering complex projects on time within enterprise-grade environments.
Guide product and development teams on data lifecycle management, experimental processes, and best practices in machine learning.
Create internal platforms and APIs that facilitate the integration of AI capabilities into customer-facing features.
Collaborate with teams to identify common patterns, anti-patterns, and tradeoffs in machine learning implementations, ensuring optimal solutions.
Build scalable, resilient services for data ingestion, event processing, and platform extension to handle large-scale data and traffic.
Contribute to the evolution of product features that process and analyze vast data sets efficiently and securely.
Write high-quality, performant, and maintainable code, ensuring thorough testing and documentation.
Mentor and collaborate with team members, fostering a culture of best practices and continuous improvement.
Work within cloud environments, designing distributed systems that are scalable, observable, and fault-tolerant.
Translate product goals into technical strategies and actionable engineering plans, coordinating with stakeholders across teams.
