Staff ML Engineer (AI)

TL;DR

Staff ML Engineer (AI): Designing, training, and deploying NLP models for core product experiences with an accent on fine-tuning large language models and optimizing production pipelines. Focus on building scalable training infrastructure, ensuring model reliability at scale, and delivering high-impact AI features for millions of daily active users.

Location: Seattle, WA (US)

Salary: $197,300–$344,700

Company

hirify.global is a leading AI CRM platform that empowers teams to drive customer success through innovative agentic AI solutions.

What you will do

• Design and execute fine-tuning strategies for LLMs and deep learning architectures tailored to NLP tasks like summarization and ranking.
• Own the end-to-end model training lifecycle, including data curation, infrastructure, evaluation, and deployment.
• Build and maintain scalable fine-tuning pipelines on GPU infrastructure.
• Collaborate with product managers, designers, and engineers to conceptualize and build new AI-driven features.
• Lead multi-functional projects and mentor other engineers to improve technical standards and code quality.

Requirements

• 5+ years of hands-on experience training and fine-tuning deep learning models in NLP or related domains.
• 5+ years of experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Proven track record of shipping fine-tuned models to production at scale.
• Proficiency in functional or imperative programming languages like Python, Go, Java, or C.
• Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Nice to have

• Expertise in recommendation systems or search.
• Familiarity with model optimization techniques like quantization, pruning, or speculative decoding.
• Experience with retrieval-augmented generation (RAG) and hybrid retrieval systems.
• Knowledge of working with structured, unstructured, and knowledge graph data types.

Culture & Benefits

• Comprehensive health benefits including medical, dental, and vision coverage.
• Support for mental health and paid parental leave.
• Retirement savings through 401(k) and employee stock purchasing programs.
• Focus on inclusive, equitable compensation and a non-discriminatory workplace.
• Opportunities to shape the future of AI and workforce transformation.