Weave Logo

Weave

Senior Machine Learning Engineer, Gen AI

Reposted 3 Days Ago
Remote
Hiring Remotely in US
Senior level
Remote
Hiring Remotely in US
Senior level
As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.
The summary above was generated by AI

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 powers 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 for 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 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.

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 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.

What Will Make Us Love You

  • A background with 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, 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

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.

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.

Top Skills

AWS
Dagster
Dvc
GCP
Gitops
Go
Iac
Java
Jupyter
Kubeflow
Kubernetes
Llms
Mlflow
Postgres
Python
Triton Server

Similar Jobs

2 Days Ago
Remote
USA
163K-274K Annually
Senior level
163K-274K Annually
Senior level
Other • Real Estate • PropTech
The Senior Machine Learning Engineer will develop, deploy, and optimize machine learning applications, collaborating with cross-functional teams to enhance AI services.
Top Skills: AWSGenerative AiLarge Language ModelsMachine LearningNatural Language ProcessingPyTorchScikit-LearnTransformersXgboost
An Hour Ago
Remote or Hybrid
8 Locations
168K-297K Annually
Senior level
168K-297K Annually
Senior level
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Lead strategy and execution for Square's next-generation websites platform using AI. Drive product roadmap, collaborate with engineers, designers, and data scientists, integrate websites with Square's commerce ecosystem, define go-to-market plans, ship high-quality experiences, and advocate for sellers to improve online presence and conversion.
Top Skills: AIFigma
An Hour Ago
Remote or Hybrid
8 Locations
153K-270K Annually
Senior level
153K-270K Annually
Senior level
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
The Senior Systems Architect will design and optimize asset management processes, leveraging AI to improve workflows and ensure compliance across digital asset channels.
Top Skills: AICatalogingDigital Asset Management SystemsGraphics DesignMetadata TaggingWorkflow Optimization

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account