Director, Machine Learning

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and expand the ML engineering team by recruiting talent, structuring pods, and creating a tech-lead layer.

• Transition the organization from ad-hoc experimentation to production-level delivery through governance of the roadmap, automated testing, on-call responsibility, and well-defined escalation/triage procedures.

• Oversee, mentor, and advance senior ML engineers and data scientists.

• Act as a representative of the ML organization to executive and cross-functional stakeholders.

• Take ownership of the technical strategy for document AI, extraction, and agentic systems pertaining to immigration case documents.

• Lead assessments regarding build versus buy decisions for ML capabilities and vendor tools, balancing factors such as cost, accuracy, latency, and compliance.

• Design and manage retrieval and context-optimization strategies, including RAG, page/section narrowing, and agentic cross-validation.

• Define and oversee the architecture of ML systems, encompassing model serving, evaluation pipelines, and feature/data infrastructure.

• Achieve measurable business results through cost reductions, enhanced document/extraction pipeline throughput, and improvements in accuracy/quality.

• Establish evaluation frameworks and quality benchmarks for LLMs prior to their production release.

• Propel ongoing optimization of model and pipeline costs.

• Collaborate with Product, Legal Operations, and Case Management leadership to convert immigration workflow requirements into ML-supported product functionalities.

• Report on the health, delivery, and cost/quality metrics of the ML organization to engineering and executive leadership.

⛳️ Requirements

• Over 8 years of experience in applied ML/AI, with several years in a leadership or management role within an ML/AI engineering team, preferably in document understanding, NLP, or search.

• Demonstrated expertise that goes beyond applied delivery, such as issued patents, peer-reviewed publications, conference presentations, or similar recognized contributions to the ML/AI domain.

• Proven history of scaling an ML/AI organization and successfully deploying production LLM, NLP, or document-extraction systems at scale, with clear accountability for cost and quality results.

• Hands-on experience with LLM and agentic systems, including RAG, context optimization, evaluation, NER/document extraction, and traditional ML techniques such as search/ranking and classification.

• Experience in making and justifying build-vs-buy decisions regarding ML capabilities.

• Background in collaborating with architects on platform-level ML infrastructure decisions.

• Familiarity with healthcare, legal, financial services, or other regulated/compliance-sensitive sectors dealing with sensitive documents is a significant advantage.

• Exceptional executive communication skills with the ability to articulate technical trade-offs in business terms for non-technical stakeholders.

• An M.S. or Ph.D. in Computer Science, Machine Learning, or a related field is preferred.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Generous vacation and paid time off policies.

• Opportunities for professional development and growth.

• Collaborative and innovative work environment.