Director, Machine Learning

Envoy Global is a proven innovator in the global immigration space. Our mission combines our industry-leading tech platform with holistic service to streamline, simplify and expedite the immigration process for employers and individuals.
Envoy Global is looking for a Director, Machine Learning to build and lead the AI/ML organization behind our immigration case management platform — including document understanding, extraction, and agentic automation across visa petitions, supporting evidence, and case correspondence. You'll grow and manage a team of ML engineers, set technical direction on build-vs-buy for AI/ML capabilities, and be accountable for the cost, quality, and throughput of every model in production. You bring not just delivery experience but recognized depth in the field — patents, publications, or equivalent proven credentials that show you can push the state of the art, not just apply it.
As our Director, Machine Learning, you will be required to:
Team & Organization Leadership
Build and scale the ML engineering organization — hiring, structuring pods, and establishing a tech-lead layer so the team can own day-to-day technical decisions as it grows.
Mature the org from ad-hoc experimentation to production-grade delivery through roadmap governance, automated testing, on-call ownership, and clear escalation/triage paths for model and pipeline issues.
Manage, mentor, and grow senior ML engineers and data scientists, and represent the ML org to executive and cross-functional stakeholders.
ML Platform Strategy & Build-vs-Buy
Own the technical strategy for document AI, extraction, and agentic systems applied to immigration case documents — petitions, supporting evidence, correspondence, and case data.
Lead structured build-vs-buy evaluations for ML capabilities and vendor tools — in-house models and pipelines versus external vendors or managed services — balancing cost, accuracy, latency, and compliance.
Design and own retrieval and context-optimization strategies (RAG, page/section narrowing, agentic cross-validation) that control LLM inference cost at scale without sacrificing accuracy.
Define and own the ML systems architecture — model serving, evaluation pipelines, feature/data infrastructure — in partnership with platform and product architects.
Delivery & Operational Impact
Be accountable for measurable business outcomes: cost savings from displacing manual review or external vendors, throughput scaling of document/extraction pipelines, and accuracy/quality gains on case-critical data.
Establish LLM evaluation frameworks and quality bars before models ship to production, and drive continuous model and pipeline cost optimization.
Partner with Product, Legal Operations, and Case Management leadership to translate immigration workflow requirements into ML-backed product capabilities.
Report on ML org health, delivery, and cost/quality metrics to engineering and executive leadership.
To apply for this role, you should possess the following skills, experience and qualifications:
8+ years in applied ML/AI, including several years leading or managing an ML/AI engineering team, ideally in document understanding, NLP, or search.
Proven credentials that demonstrate depth beyond applied delivery — issued patents, peer-reviewed publications or conference talks, or equivalent recognized contributions to the ML/AI field.
Track record scaling an ML/AI organization and shipping production LLM, NLP, or document-extraction systems at volume, with clear ownership of cost and quality outcomes.
Hands-on depth in LLM and agentic systems (RAG, context optimization, evaluation), NER/document extraction, and traditional ML (search/ranking, classification) — comfortable going deep with the team, not just directing from above.
Experience making and defending build-vs-buy calls for ML capabilities, and partnering with architects on platform-level ML infrastructure decisions.
Experience in healthcare, legal, financial services, or other regulated/compliance-sensitive domains handling sensitive documents is a strong plus.
Excellent executive communication skills; able to translate technical trade-offs into business terms for non-technical stakeholders.
M.S. or Ph.D. in Computer Science, Machine Learning, or a related field preferred.
Annual Salary Range: $200,000-$245,000
This position is 100% remote, working from home, within the United States.
Notice at Collection for California Applicants:
http://www.envoyglobal.com/notice-at-collection-for-ca-applicants

Work arrangement
Yes