Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building core ML foundations for Nova’s agentic experiences with an accent on retrieval systems, evaluation frameworks, and model integration. Focus on operationalizing RAG use cases, developing generalized evaluation frameworks, and productionizing AI features for reliability and scale.

Location: Must be based in the US (Atlanta, Austin, Boston, Chicago, Denver, New York, or San Francisco)

Salary: $133,500 - $212,000

Company

hirify.global is an AI-powered customer engagement platform helping brands create individualized experiences at scale.

What you will do

• Design and build ML platform components for agentic systems, including retrieval pipelines and indexing strategies.
• Operationalize RAG use cases from data sourcing and embedding generation to runtime retrieval.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics and monitoring.
• Implement reusable abstractions and tooling to enable efficient building of ML-powered experiences.
• Partner with backend engineers to productionize ML features with strong reliability and observability.
• Prototype applied ML solutions to validate feasibility before full-scale investment.

Requirements

• 5+ years of experience as a Machine Learning Engineer focused on production systems.
• Strong engineering skills with Python or TypeScript, including frameworks like Mastra.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Proven track record of integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Must be based in the US (specific cities listed in location).

Nice to have

• Experience building ML/LLM platforms or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability and proactive regression detection.
• Background in personalization, recommendations, or applied NLP.

Culture & Benefits

• Competitive salary, meaningful equity, and 401(k) plan.
• Comprehensive medical, dental, vision, and life insurance.
• Balance Days (additional paid holidays) and flexible PTO.
• Paid sabbatical and fertility/adoption assistance.
• Monthly allowances for employee wellness and professional development.
• Complete laptop workstation provided.