обновлено 6 дней назад
Machine Learning Engineer V (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer V (AI): Building and scaling production-grade agentic platform capabilities, LLM application frameworks, and AI-enabled workflows for tax compliance products with an accent on reliability, security, evaluation, and enterprise-scale operations. Focus on designing orchestration patterns, integrating tools and retrieval systems, measuring agentic quality and safety, and mentoring engineers while maintaining high-availability services.
Location: United States
Company
provides a cloud compliance platform for tax technology, processing customer API calls and tax returns at enterprise scale.
What you will do
- Design, build, and operate foundational agentic platform capabilities for Aviator, the Avi Agent, and other AI-powered experiences.
- Develop scalable LLM application frameworks, orchestration patterns, tool integrations, retrieval systems, and agent workflows.
- Create evaluation methods covering quality, accuracy, latency, cost, safety, and task completion.
- Translate ambiguous product and business needs into technical designs, prototypes, production features, and measurable outcomes.
- Apply CI/CD, automated testing, code review, documentation, observability, and operational readiness practices.
- Partner with product, engineering, security, data, and business stakeholders; mentor engineers and improve high-availability systems.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a closely related technical field.
- 8+ years of professional experience building, deploying, and operating production software systems, with strong preference for Python.
- Hands-on experience building LLM applications, agentic systems, or AI-enabled workflows in production or production-like environments.
- Practical experience with GPT, Claude, Llama, or similar LLMs, including prompting, orchestration, evaluation, and reliability.
- Experience with enterprise-scale software design, distributed systems, data structures, design patterns, high-availability operations, and AWS, Azure, or GCP.
- Familiarity with MCP, A2A, tool use, retrieval, multi-agent orchestration, AI governance, evaluation, auditability, and responsible data handling.
Culture & Benefits
- AI is embedded in engineering workflows, decision-making, and products.
- Compensation package with paid time off and paid parental leave.
- Many employees are eligible for bonuses.
- Benefits generally include private medical, life, and disability insurance, varying by location.
- Commitment to diversity, equity, inclusion, and employee resource groups.
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