Avride
Labeling Backend Software Engineer
Austin, Texas · Mid · Internship
Sponsorship not specifiedDetected 2 days ago
PythonC++DjangoFastAPIDistributed SystemsBackend DevelopmentData StructuresAlgorithmsPostgreSQLAWSCloud PlatformsDockerKubernetesMachine LearningSparkAirflowAI OrchestrationRoboticsSensors
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 10 green-card filings in this occupation, 100% were for a worker who already held the job.
Green-card follow-through: 88%
Of 8 labor certifications old enough to have been used, 1 expired without the employer filing the next step. Median time from filing to decision: 459 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
DOL often reclassifies their job titles
The Department of Labor assigned a different occupation than this employer requested on 79% of its 19 wage determinations — against a 18% norm. The occupation sets the prevailing wage floor.Reclassification is routine and can reflect genuinely hybrid roles; it is not by itself evidence of underpayment.
Files H-1B transfers
6 transfer filings in the last year, covering 6 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- You'll operate independently, make architectural tradeoffs, and help raise the bar for the engineers around you.
- This is a hands-on individual contributor role: you will spend most of your time designing, writing, and shipping code.
Responsibilities
- Design, build, and own backend systems that manage the full lifecycle of labeled data, from ingestion to delivery, including core Python services, APIs, and databases.
- Build and scale data preparation and labeling pipelines that transform massive sensor streams (lidar, camera, radar) into label-ready formats, and manage annotation workflows at scale using both automated and human labeling with modern orchestration frameworks.
- Design and implement robust integrations with external vendors and internal tools so data and feedback flow seamlessly across labeling workflows.
- Develop automated validation and QA systems that safeguard dataset integrity, monitor quality, and surface key performance insights.
- Partner with ML and Perception teams to turn evolving requirements into scalable data solutions that directly drive model improvements.
- Lead technical design for your area, review code, and mentor other engineers on the team.
- 4+ years of professional software engineering experience building and operating backend services in production (internships and academic projects don't count toward this).
- A track record of owning services end-to-end: design, implementation, deployment, monitoring, and on-call.
- Solid grounding in system design, algorithms, and data structures, applied to real systems at scale.
Requirements
- Strong proficiency in Python, including backend frameworks and asynchronous stacks (asyncio, aiohttp, FastAPI).
- Production experience with relational databases (preferably PostgreSQL): schema design, query optimization, ORMs (e.g., SQLAlchemy, Django ORM), and migrations (e.g., Alembic).
- Hands-on production experience with cloud platforms, containerization (Docker, Kubernetes), and cloud object storage (AWS S3, GCS, etc.).
Nice to have
- Experience with workflow orchestration (Argo, Airflow, etc.)
- Experience with large-scale distributed systems or products
- Big data and distributed data-processing tooling (Spark, PyArrow, etc.)
- Experience working with 3D sensor data (point clouds, sensor fusion, etc.)
- Previous work in AV, robotics, or ML-heavy environments
- C++ development experience
- Avride is an equal opportunity employer and committed to providing reasonable accommodations to qualified applicants and employees with disabilities to ensure they have equal access to employment opportunities.
Company info
- Avride is at the forefront of autonomous mobility, developing and deploying self-driving cars and delivery robots that are shaping the future of transportation and logistics.
- Our Labeling Backend team builds the data infrastructure behind the massive sensor datasets that power our perception and ML pipelines.
- The services we build support both automated and human-in-the-loop labeling workflows, delivering the high-quality labeled data our models depend on so our vehicles and robots keep improving at scale.
Visa & Work Authorization
- Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.
This listing is sourced directly from Avride's careers page and normalized into a canonical job model.