Machine Learning Engineer (AI/LLM)

Location: Pleasanton, California, USA; hybrid Flex Work with at least 50% of each quarter spent in the office or in the field

Salary: $160,000–$240,000 USD annual base salary for the primary location; additional US locations have a base range of $136,200–$240,000 USD

Company

hirify.global is a Fortune 500 company developing AI-powered software for managing people, money, and enterprise operations.

What you will do

• Design and implement features for machine learning platforms, pipelines, and production services.
• Develop tailored user experiences using agentic AI, large language models, natural language understanding, and retrieval-augmented generation.
• Build ETL pipelines and inference services covering data processing, model fine-tuning, deployment, and evaluation.
• Develop and deploy scalable APIs and services with Docker and Kubernetes.
• Evaluate, scale, and monitor ML features and cloud-based machine learning architectures.
• Collaborate with product managers, application teams, engineers, and leadership to deliver ML solutions across the product ecosystem.

Requirements

• Bachelor’s degree in engineering, data or computer science, physics, mathematics, or an equivalent field; advanced degrees are preferred.
• At least 3 years of professional experience building machine learning products from applied research through production.
• At least 3 years of production experience with Python, ETL pipelines, inference services, LLMs, and text generation models.
• At least 3 years of experience with data engineering, Pandas or PySpark, Kubernetes, Docker, and cloud platforms such as AWS or GCP.
• Experience with machine learning and deep learning frameworks including PyTorch, TensorFlow, or scikit-learn.
• Strong understanding of statistical analysis, supervised and unsupervised learning, natural language processing, and information retrieval or recommendation systems.

Nice to have

• Master’s degree or PhD in a relevant technical discipline.
• Experience building information retrieval systems.
• Experience with autonomous agents, orchestration frameworks, and advanced LLM or RAG applications.

Culture & Benefits

• Flexible hybrid work combining office, field, and remote time according to team and role needs.
• Opportunity to work on AI platform capabilities and applications used by millions of people.
• Potential eligibility for a bonus plan or role-specific commission or bonus.
• Annual refresh stock grants may be included in the total compensation package.
• Reasonable accommodations are available during the application process.