Does Weave sponsor H-1B visas?
Check real filing data, salaries & approval rates on VisaTalentUSA
Job Description
Key Skills Required
Master these to land this role
Want to know if you're a match for this job?
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.
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.
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'll 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.
- 3-5 years of experience in Machine Learning or AI, preferably with a focus on natural language.
- 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 at scale for external products and customers.
- 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, LLM evaluations, multi-modal models, and others.
- Experience with data labeling or annotation for audio or text use cases.
- Understanding of distributed systems and building scalable, redundant, and observable services.
- Expertise in designing 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.
- Demonstrated capacity for leadership or mentorship.
- 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 engineering and systems with strong proficiency in coding and system design.
- Experience with low-latency natural language models and pipelines 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. 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.
- 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.
How would you rate this job post?
See what other professionals think about this role.
Similar Opportunities
AI Clinical EHR Vignette Evaluator (Physician) – Project-Based Opportunities
mindrift
IndiaAI Training and Evaluation Expert (Insurance Underwriting & Claims)
weekday
IndiaSenior Backend Engineer (AI Infrastructure)
Sentient Foundation
BangaloreRemote Software Engineer at Texas Sports Academy
Texas Sports Academy
IndiaMore Openings at Weave
Explore Top Companies in this Space
Included Health
HealthTech & Virtual Care Platforms / Digital Patient Navigation / Behavioral Health & Care Coordination / B2B Enterprise SaaS
Zenara Health
AI-Native Psychiatric Practice Software & SaaS / Mental Health Clinical Decision Support / Care Management & Remote Patient Monitoring (RPM) / HealthTech Infrastructure
Virta Health
Digital Therapeutics & HealthTech / Chronic Disease Reversal SaaS / Virtual Care & Remote Patient Monitoring / Corporate Health Benefits
RadiantGraph
Healthcare AI & Patient Engagement SaaS / Clinical Data Intelligence & Personalization / HealthTech & Marketing Automation Tools / HIPAA-Compliant Conversational Voice Agents
Weave
View Company ProfileWeave is a premier, all-in-one patient communication and engagement software platform specifically engineered to transform how small and medium-sized healthcare practices operate. Founded in 2011 and headquartered in Lehi, Utah, the company fundamentally eliminates the need for fragmented legacy systems. Under the hood, Weave unifies VoIP phone systems, two-way SMS texting, automated appointment scheduling, digital intake forms, seamless payment processing, and online review management into a single, highly intuitive interface. Their primary target audience spans dental offices, optometry clinics, veterinary hospitals, and specialty medical practices that need to dramatically reduce front-desk burnout and administrative overhead. What sets Weave apart in the rapidly expanding HealthTech landscape is its deep, seamless integration with industry-specific Electronic Health Records (EHR) and practice management systems, turning everyday patient interactions into a highly automated, revenue-driving engine while delivering a frictionless patient experience.
Safety First
- Never pay for a job application.
- Do not share sensitive bank info.
- Verify the client before starting work.
