Staff Machine Learning Engineer (AI)

TL;DR

Staff Machine Learning Engineer (AI/LLM): Building and optimizing large-scale SID, ASR, and NLP systems for meeting transcription and conversational intelligence with an accent on scaling ML systems and production-ready AI features. Focus on designing training and inference strategies for LLMs and speech models while balancing quality, latency, and cost.

Location: Hybrid in Mountain View, CA

Salary: $278,000 – $330,000 USD per year

Company

hirify.global is a world-leading tool for AI-powered meeting transcription, summarization, and collaboration.

What you will do

• Architect and evolve large-scale SID, ASR, NLP, and LLM systems powering summarization, chat, and speech understanding.
• Lead the design and implementation of training, fine-tuning, and inference strategies using PyTorch and/or JAX.
• Own the end-to-end ML system lifecycle from research prototyping to production deployment and monitoring.
• Collaborate with product and infrastructure teams to translate cutting-edge research into scalable production-grade systems.
• Drive system-level improvements in model performance, robustness, and observability using real-world conversational data.
• Mentor other engineers and set technical direction for ML infrastructure, data pipelines, and deployment workflows.

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field with 10+ years of relevant industry experience (PhD preferred).
• Deep hands-on experience building and fine-tuning foundation models, specifically in ASR, TTS, multimodal, or modern LLM/NLP systems.
• Strong command of modern ML research with the ability to evaluate and implement production-worthy innovations.
• Extensive experience deploying, scaling, and operating ML systems in production across training and serving infrastructure.
• Proficiency in working with large-scale speech and conversational datasets, including preprocessing and quality analysis.
• Must be based in or able to work in a hybrid setup in Mountain View, CA.

Nice to have

• Experience with agentic systems, tool-use frameworks, or multi-model orchestration.
• Experience with personalization, recommendation systems, or user modeling.

Culture & Benefits

• Work alongside industry-veteran scientists and engineers in a core AI team.
• Directly influence applied research and technical roadmaps for cutting-edge AI technology.
• Comprehensive total rewards package.
• Inclusive and diverse work environment as an equal opportunity employer.