As a Staff Software Engineer, you'll lead the architecture and implementation of core systems and data platforms, ensuring adaptability and planning technical strategies.
Hivemapper is a decentralized global map data network built by 10s of thousands of mapping devices. High-res sensors like RGB, Stereo Depth, GNSS, IMU, etc. feed sensor fusion and ML models at the edge. Data is automatically uploaded in near realtime over LTE or WiFi. Enterprise tech, mapping, auto, robotaxis, rideshare, and entertainment represent some of the customers consuming data today.
APIs allow anyone to consume precisely extracted Map Features, HD map data, high-res street-level imagery, construction, and driving events for AV simulation. Tech-savvy customers develop and deploy software directly to our dashcams to get realtime data for things like change detection or visual semantic data mining. AI Fleet management tools drive value to large fleets of vehicles.
Data Platform
Every day, we process data from millions of KM from 10s of thousands of high resolution sensors deployed around the world. A symphony of different Sensor Fusion, ML, AI, and 3D Sensing processes are performed at the edge, feeding an AI conflation system on our processing clusters called Map AI.
The Platform Engineering team is responsible for the core distributed systems, ML infrastructure, data model abstractions, and data engine that powers our data customers, consumer products, and user-facing AI technology.
We strongly believe in engineering design principles around abstraction and programmability that allow us to move quickly with minimal manual interventions. Our work is fast-paced, collaborative, and data-driven.
Responsibilities
- Drive architecture, design, implementation, and eval of our core systems and data platforms
- Partner across the company to ensure our systems are adaptable to emerging opportunities
- Help plan technical roadmaps and lead higher level technical strategy
Requirements
- Experience building production critical systems used by >= thousands of users
- Deep backend experience with a large scale data platform, DB, ETL, distributed system, etc.
- Strong analytical skills in a relevant field like ML, math, statistics, quantitative economics, etc.
- Track record of deploying and maintaining large scale distributed systems
Nice to Haves
- Experience with geospatial data, HD mapping, sensor fusion, ADAS or AV, etc.
- Experience managing, generating, and processing large amounts of geospatial or imagery data
- Experience with Spark, EMR, MapReduce, Presto, Trino, Mongo Sharding, or similar systems
- Experience with blockchain/web3Experience scaling products or systems at hyper-growth startups
What We Offer
- Medical, dental and vision benefits plus FSA
- Family leave
- 401(k) program
- Unlimited Flex PTO
- Commuter benefits
- Paid lunch
Hivemapper San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Develop highly scalable Java software for ServiceNow’s platform persistence systems. Manage data lifecycles, storage, retrieval, security, performance, and recovery across relational and distributed systems. Collaborate cross-functionally on data initiatives, telemetry, visualization, and Kubernetes deployments while applying concurrency, parallel programming, and AI-assisted development practices.
Top Skills:
Amazon S3Apache IcebergJavaJavaScriptKubernetesRelational DatabasesServicenow Platform
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Build and operate a security data platform connecting SIEM, identity, asset, threat intelligence, and knowledge graph systems. Design core APIs, distributed data pipelines, schemas, risk scoring, entity resolution, and coverage queries. Own architecture and platform workstreams from scoping through delivery, collaborate with detection and identity teams, review code, mentor engineers, and drive partner adoption. The role requires expert Python, deep Splunk expertise, cybersecurity experience, and senior-level project ownership.
Top Skills:
Asset InventoryAsynchronous Data PipelinesIdentity GovernanceKnowledge GraphsLarge Language ModelsMachine LearningMessage BusMitre Att&CkPythonRetrieval-Augmented GenerationSchema RegistrySIEMSplSplunkSplunk Apis
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Lead architecture, roadmap, and implementation for Veza’s scalable Access Graph data platform. Solve complex distributed-systems and graph-database challenges, establish engineering standards, improve reliability and performance, and deliver backend services in Go. Drive cross-team planning, technical decisions, design reviews, and stakeholder alignment while mentoring engineers and team leads. Ensure high standards for correctness, testing, documentation, support, rollback safety, and responsible use of AI-assisted engineering tools.
Top Skills:
AWSAzureClaude CodeDockerGCPGithub CopilotGoGraph DatabasesKubernetesMicroservicesNeo4JOlapOltpRestful Apis
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
