Job description

Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways. You will be joining a team of talented developers that share a common interest in distributed backend systems, data, scalability, and continued development. You will get a chance to apply these and other skills to new and ongoing projects to make machine learning more approachable, data more available, and easier to discover and use by helping design how teams build out AI-powered features at Weave. Our teams are cross-functional agile teams composed of a product owner, backend and frontend devs and DevOps. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest. Above all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture. PURPOSE The Machine Learning Team's mission is to enable product innovation by making it painless for developers to build AI-powered applications that require access to large sets of data. Machine learning is challenging, but we are striving to democratize access to the tools and technology that power it so teams can build cutting-edge features safely and responsibly without a PhD in Data Science. As a Machine Learning Engineer on the team, you’ll be building models for new products with emerging technologies, at scale. We handle data for hundreds of millions of people daily. - This position will be available fully remote in the US with an opportunity to work in an office if located near the Lehi, UT Headquarters. - Reports to: Engineering Director What You Will Own - 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 trade-offs 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. What You Will Need to Accomplish the Job - High integrity, team-focused approach, and collaboration skills to build tight-knit relationships across Weave with various roles and stakeholders. - Responsive person with a strong bias for action. - 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 100 M to 10 B 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, multimodal 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 experience working in enterprise-grade production environments. - Strategic thinker with a strong technical aptitude and a passion for execution. What Will Make Us Love You - A background in data analysis, visualization, and presentation. - 3+ years of experience in data science, machine learning, or predictive analytics in addition to engineering experience. - Experience with natural language models, embeddings, and inference in production, at scale. - Experience with real-time audio models and voice use cases such as transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis. - Experience with emerging technologies such as Model Context Protocol (MCP). - Proficient understanding of containers, orchestrators, and usage patterns at scale, including networking, storage, service meshes, and multi-cluster communication. Experience with Kubernetes or GKE and the Operator Pattern (GCP), specifically, is a plus. - Experience with highly sensitive data such as PHI (HIPAA) and PII data. - Experience with automation and container-based workflow engines. - Experience with GitOps, IaC, and configuration-driven systems. - A preference for open source solutions. - A track record of clean abstractions and simple-to-use APIs. - Deep understanding of distributed data technologies such as streaming, data mesh, data lakes, warehouses, or distributed machine learning. - A desire to advance the state of the art with new and innovative technologies. - Enjoys working in a greenfield environment using rapid prototyping. - Enjoys working with open-ended, evolving problems and domains. #LI-DNI Employment with Weave is contingent upon the successful completion of a background check, conducted in accordance with applicable laws. At Weave, we use Artificial Intelligence (AI) tools to help us work more efficiently and create a smoother candidate experience. AI may assist with things like writing job descriptions, scheduling interviews, or reviewing applications against job-related criteria. For additional information, please review the External AI Policy Statement available on our Careers page. Weave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know. Beware of recruitment fraud. All official correspondence will occur through Weave branded email. We will never ask you to share bank account information, cash a check from us, or purchase software or equipment as part of your interview or hiring process.

Requirements

Must-haves

Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways.
Our teams are cross-functional agile teams composed of a product owner, backend and frontend devs and DevOps. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest.
Above all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture.
Reports to: Engineering Director
What You Will Own
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 trade-offs 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.
What You Will Need to Accomplish the Job
High integrity, team-focused approach, and collaboration skills to build tight-knit relationships across Weave with various roles and stakeholders.
Responsive person with a strong bias for action.
Experience moving and storing TBs of data or 100 M to 10 B 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, multimodal models, and others.
Experience with data labelling or annotation for audio or text use cases.

Nice-to-haves

5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaiagilegojavapythonmlpostgresawsgcpkubernetes

Platform: ashby
Effort: quick