Jobs / United States / Abbott Laboratories
Sr. Engineer, AI Platform
Abbott Laboratories · 🇺🇸 United States - Wisconsin - Madison
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 73 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 28 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 Abbott Laboratories paid sponsored hires in similar roles3 certified filings for “STAFF SOFTWARE ENGINEER” (Software Developers) in TX: $135k–$158k, median $143k. Most were filed at wage level II (33%) — 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 — Abbott Laboratories
The US Department of Labor certified 73 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 28 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 Abbott Laboratories →
About the role
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The Sr AI Platform Infrastructure Engineer is a pivotal position for driving the strategic vision and technical execution for the Cancer Diagnostics AI/ML platform. The role is accountable for the architecture, reliability, scalability, security and cost of every layer beneath the platform's applications, from the cloud, network and compute foundation to the serving, orchestration and streaming systems that workloads run on. This engineering leader partners closely with the AI Platform Software and Safety leads to own and develop the AI/ML platform. This role architects, builds and operates AI infrastructure as software, supporting large language models, predictive models, agentic systems and traditional software applications across the MLOps lifecycle. This is a hands-on engineering role that requires a technical leader to demonstrate ownership, accountability and leadership. This role is based in Madison, WI . Essential Duties Include, but are not limited to, the following: • Design and own the platform's cloud and Kubernetes foundation, including account and network topology, VPC and subnet design, private connectivity, ingress and egress control, DNS and certificates, and the provisioning, upgrade, migration, multi-tenant isolation and security of production clusters. • Lead the platform's expansion across clusters and regions, covering topology, identity federation, state and data placement, traffic management and failure domains, and evaluate multi-cloud where business need warrants it. • Own infrastructure-as-code and GitOps for the platform, including module design, state management, environment promotion, drift control, and the testing and rollback of infrastructure changes; build and operate the CI/CD and deployment tooling that platform software releases run on in partnership with the AI Platform Software lead. • Architect, build and operate production model serving and GPU infrastructure for large language and predictive models, including scheduling, multi-tenancy, autoscaling, low-latency serving, inference optimization (quantization, batching, graph compilation), and capacity planning and cost attribution for shared compute. • Partner with the AI Platform Software and Safety leads on the model lifecycle by providing the infrastructure it runs on, including reproducible data, feature and training pipelines with dataset-to-model lineage, promotion environments, the traffic-shifting and rollback mechanisms behind canary, shadow and A/B rollout, and pipeline enforcement of the evaluation and promotion gates. • Architect, build and operate workflow orchestration and event-streaming infrastructure, including workflow and state-machine design, event-driven triggers and scheduling, retries and idempotency, topic and partition design, schema management, delivery semantics and cross-region replication. • Own the observability stack and service level objectives for infrastructure services, with proactive detection across the platform; lead disaster-recovery strategy as a business tradeoff between cost and recovery time and recovery point objectives; and serve as the escalation point for complex infrastructure incidents, leading the post-incident analysis that drives systemic reliability improvements. • Own infrastructure security and governance, including least-privilege identity, secrets management, network policy, workload