Jobs / United States / Salesforce INC
Member of Technical Staff — Machine Learning & Agent Security Engineering
Salesforce INC · 🇺🇸 2 Locations
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 1,544 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 498 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 Salesforce INC paid sponsored hires in similar roles9 certified filings for “Manager, Technical Support Engineering” (Information Technology Project Managers) in IN: $139k–$164k, median $158k. Most were filed at wage level III (44%) — 3 lottery entries, ≈46% 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 — Salesforce INC
The US Department of Labor certified 1,544 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 498 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 Salesforce INC →
About the role
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Member of Technical Staff — Machine Learning & Agent Security Engineering Job Category: Software & Security Engineering About Salesforce We’re Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. About the Team We are a security agentic & machine learning engineering team within the Salesforce Security organization, building scalable and resilient AI and ML capabilities for security engineering. We are looking for a hands-on Member of Technical Staff (MTS) — Machine Learning and Agent Engineering to contribute to our platform for Security AI and automated Agentic Trust workflows. The ideal candidate is a strong Python Software and Security Engineer with practical machine learning and Agentic experience who enjoys building reliable production systems and applying emerging Agentic AI technologies to real-world engineering and security problems. You will work within established team architectures and technical direction to deliver well-scoped capabilities, solve implementation challenges, and operate the software you build. Your Impact 1. Agentic and AI Security Engineering Architect, develop, and operate high-availability production AI and LLM agentic systems, applying tool calling, structured outputs, and state management in Python across public cloud environments. Deliver reliable, well-tested AI services and APIs, turning emerging agentic patterns into robust software solutions. 2. Scalable Security Intelligence Engineer high-throughput data-processing pipelines, feature workflows, and automated security intelligence systems capable of processing large-scale security telemetry seamlessly. Operationalize machine learning models (classification, clustering, anomaly detection) to accelerate security automation and threat detection at Salesforce scale. 3. Operational Ownership & Resilience Take full end-to-end ownership of systems across implementation, testing, deployment, and live production operations. Drive system resilience, observability, and performance through robust telemetry (logs, metrics, traces) and an attacker's mindset. Required Qualifications 3+ years of professional software engineering, machine learning engineering, or related development experience. Strong hands-on programming skills in Python. Solid software engineering fundamentals, including data structures, APIs, testing, debugging, code reviews, and maintainable software design. Experience building and operating production software, services, data-processing systems, or ML applications. Experience solving implementation-level challenges involving scale, performance, reliability, data volume, or concurrency. Practical understanding of ma