Home › Companies › Matter Intelligence › Data/ML Infrastructure Engineer
Data/ML Infrastructure Engineer
Matter Intelligence · San Francisco · On Site · Active · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Matter Intelligence |
| Title | Data/ML Infrastructure Engineer |
| Normalized title | - |
| Department / team | Software Engineering / Software Engineering |
| Location | San Francisco, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-18 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Matter Intelligence. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Software Engineering. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Matter Intelligence |
| Source | df790fd5-fafa-4c97-b8d5-37e1b18e602e |
| ATS provider | Ashby |
Description
About the Role We are seeking a Data Infrastructure Engineer to build and operate the infrastructure that turns drone, aerial, and orbital sensing data into production datasets, models, and customer-facing insights. This role spans ingestion, processing, storage, compute, and serving, with a strong emphasis on reliability, observability, performance, and cost.
You will work closely with research and product engineering to shorten iteration cycles, improve reproducibility, and raise the quality bar for production systems. You will define clear interfaces and operational standards that keep the platform trustworthy as data volume, model complexity, and product usage scale.
What You’ll Do Design, build, and operate scalable data and ML infrastructure on AWS, including workloads running on Kubernetes
Build and maintain systems for ingestion, processing, storage, and serving, with strong guarantees around data quality, correctness, and operational safety
Partner closely with research to support perception model training and evaluation workflows, enabling faster experimentation and more reproducible iteration
Build platform primitives for observability, data versioning, lineage, evaluation, reproducibility, and operational excellence
Partner with product engineering to ensure data- and model-derived insights are accessible through reliable, low-latency serving and retrieval interfaces
Design systems that enable efficient access patterns for customer-facing products, including search, indexing, and large-scale querying
Identify and address bottlenecks in throughput, cost, and operational complexity as the platform scales
What We’re Looking For You have strong software engineering fundamentals and have built production systems where reliability, cost, and performance matter. You can reason clearly about distributed systems tradeoffs, and you have experience designing data-intensive infrastructure that other engineers depend on.
You are comfortable working across data platform and ML platform concerns, and you understand how tightly coupled they become in production. You care about reproducibility, debuggability, and developer experience because you have seen how quickly they become bottlenecks.
You work effectively across research and product teams. You can translate ambiguous needs into clear interfaces and systems, and you can drive work from design through production while maintaining a high quality bar.
A few things we expect in this role:
Meaningful experience building production data infrastructure, ML infrastructure, or distributed systems
Strong programming skills in Python and SQL, with the judgment to choose the right abstractions and interfaces for production systems
Experience building and operating systems on AWS
Familiarity with modern infrastructure and platform tooling, including Kubernetes, Docker, and Terraform
Experience working with production storage and serving systems such as Postgres and Redis
Familiarity with data and ML workflow tooling such as Metaflow
Strong instincts for observability, testing, and operational excellence
Nice to Have Experience supporting ML training, evaluation, batch inference, or model deployment in production
Familiarity with modern large-scale data patterns and tooling, including streaming, backfills, partitioning strategy, and schema evolution
Experience building internal platform primitives such as data versioning and lineage, dataset curation, experiment tracking, or tooling for reproducible workflows
Exposure to perception, multimodal, or geospatial systems, especially where data originates from real sensors and is used in real products
Location This is a full-time role based in San Francisco, CA.
ITAR Requirements To comply with U.S. export regulations, applicants must be one of the following:
A U.S. citizen or national
A lawful permanent resident (green card holder)
Eligible to obtain required authorizations from the U.S. Department of State
Employee Offerings & Benefits At Matter, we believe in rewarding high performance and providing the support you need to thrive. Our compensation and benefits package includes:
Competitive compensation based on experience
Early-stage equity package
100% employer-paid health, dental, and vision coverage
Opportunity to work on novel sensing, data, and AI systems with real-world deployment paths across drone, aerial, and orbital platforms
Who You Are You are a strong engineer who likes building reliable systems that other teams can trust. You care about infrastructure quality, operational rigor, and clear interfaces. You are energized by working close to the data, close to the models, and close to the product.
Full job record
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| Provider | ashby |
| Provider Job Key | 976f195b-f676-4207-8a74-ee0ab42837e3 |
| Title | Data/ML Infrastructure Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Francisco |
| Department | Software Engineering |
| Team | Software Engineering |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/matter-intelligence/976f195b-f676-4207-8a74-ee0ab42837e3 |
| Apply URL | https://jobs.ashbyhq.com/matter-intelligence/976f195b-f676-4207-8a74-ee0ab42837e3/application |
| First Seen At | 2026-05-29 06:52:40Z |
| Last Seen At | 2026-06-18 10:28:17Z |
| Last Checked At | 2026-06-18 10:28:17Z |
| Last Changed At | 2026-05-29 06:52:40Z |
| Inactive At | — |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=matter-intelligence/date=2026-06-18/2026-06-18T10-28-06-890Z-f0ffa53f190684e0fa32d5ee286fdb9a0dab8c09970853b774e63d4b088fa0de.json |
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