Machine Learning Engineer (LLM)

TL;DR

Machine Learning Engineer (LLM): Building and optimizing large-scale SID, ASR, NLP, and LLM systems for meeting transcription and conversational intelligence with an accent on model architectures, training strategies, and production-grade scalability. Focus on designing and implementing fine-tuning and inference strategies, owning the end-to-end ML lifecycle, and translating research into scalable product features.

Location: Hybrid in Mountain View, CA

Salary: $196,000 – $221,000 USD per year

Company

hirify.global is a leading AI-powered tool for real-time 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 JAX.
• Improve model architectures, loss functions, and decoding strategies based on research and production constraints.
• 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, high-impact systems.
• Mentor other engineers and set technical direction for ML infrastructure and data pipelines.

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field with 3+ years of relevant industry experience (PhD preferred).
• Deep, hands-on experience building, fine-tuning, and post-training large language models or foundation models.
• Extensive experience deploying, monitoring, and operating ML systems in production.
• Significant experience in at least one: ASR, TTS, Multimodal foundation models, or modern LLM NLP tasks.
• Ability to work with large-scale speech and conversational datasets, including preprocessing and quality analysis.
• Experience scaling ML systems across training, inference, and serving infrastructure.

Nice to have

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

Culture & Benefits

• Opportunity to work alongside industry-veteran scientists and engineers on cutting-edge AI technology.
• Culture of strong technical decision-making, execution, and mentorship.
• Comprehensive total rewards package including base salary and benefits.
• Inclusive and diverse work environment as an equal opportunity employer.