Jobs / United States / Chime Financial INC
Senior Software Engineer, Machine Learning Platform
Chime Financial INC · 🇺🇸 San Francisco, CA, USA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 81 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 20 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Chime Financial INC paid sponsored hires in similar roles21 certified filings for “Software Engineer” (Software Developers) in CA: $175k–$225k, median $200k. Most were filed at wage level II (48%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Chime Financial INC
The US Department of Labor certified 81 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 20 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Chime Financial INC →
About the role
About the role Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently. As a Senior Software Engineer on the Machine Learning Platform team, you will design and build scalable systems spanning traditional machine learning and emerging AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic orchestration. You’ll work at the intersection of distributed systems, cloud infrastructure, applied machine learning, and AI product engineering. This role focuses on creating secure, reliable, and reusable platform capabilities that help teams choose the right approach, from conventional predictive models to LLM-powered and multi-step agentic systems, while maintaining strong standards for evaluation, observability, governance, privacy, and cost efficiency. In this role, you can expect to • Design, build, and operate scalable ML and AI infrastructure on AWS. • Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration. • Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis. • Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost. • Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap. • Build distributed training, batch inference, and large-scale processing systems using frameworks such as Ray or Spark. • Build and maintain infrastructure as code using Terraform. • Support and evolve the feature store and feature pipelines. • Develop data ingestion and streaming systems using technologies such as Kinesis, Kafka, Flink, or Spark. • Improve CI/CD workflows for ML models, AI applications, and platform components. • Partner closely with Data Science and ML Engineering teams to improve developer experience. • Participate in on-call rotations to support production systems. To thrive in this role, you have • Knowledge of the machine learning development lifecycle, including data preprocessing, model training, evaluation, deployment, and monitoring. • Experience designing distributed systems and large-scale data or compute platforms on AWS using frameworks such as Spark or Ray. • 5+ years of experience in ML or AI infrastructure, platform engineering, distributed systems, or production ML systems. • Working knowledge of LLM application patterns such as retrieval-augmented generation, structured outputs, tool calling, agent orchestration, and evaluation of non-deterministic systems. • Experience designing production systems that integrate ML or foundation models through reliable APIs, workflows, and data contracts. • Hands-on experience with CI/CD pipelines, DevOps practices, and infrastructure as code. • Experience with containerization and orchestration technologies such as Docker and Kubernetes. • Strong programming skills in Python, Go, Scala, Java, or similar languages. • Solid understanding of software engineering fundamentals, including testing, version control, code review, and observability. Nice-to-have • Experience shipping LLM-powered or agentic systems to production. • Experience with one or more