Senior/Lead Machine Learning Engineer (AI/ML)

TL;DR

Senior/Lead Machine Learning Engineer (AI/ML): Designing and building cutting-edge AI/ML solutions for enterprise AI products with an accent on the full ML lifecycle from ideation to deployment. Focus on transforming research prototypes into scalable, production-grade AI/ML services that generalize across hirify.global customers and influencing product direction through collaboration with product managers.

Location: Palo Alto, California, US. For roles in San Francisco and Los Angeles, specific ordinances apply.

Company

hirify.global AI Research focuses on designing and building cutting-edge AI/ML solutions powering enterprise AI products.

What you will do

• Design, implement, and evaluate LLM-based and classical ML systems for enterprise use cases.
• Transform research prototypes into scalable AI/ML services for hirify.global customers.
• Collaborate with engineers, researchers, and cross-functional partners to build data, model, and deployment pipelines.
• Partner with product managers and stakeholders to understand customer needs and influence product direction.
• Lead technical discussions, drive prioritization, and ensure timely delivery of ML features.
• Mentor junior engineers on technical design, implementation, and engineering best practices.

Requirements

• MS or Ph.D. in a quantitative discipline with 3+ years, or BS with 5+ years, of industry experience building ML production systems.
• Strong experience designing, training, and evaluating machine learning models with large-scale datasets.
• Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch).
• Proven experience building scalable, production-grade machine learning services.
• Experience in one or more ML domains such as LLMs, NLP, deep learning, or classical machine learning.
• Experience applying ML techniques in real-world applications like conversational AI or recommendation systems.
• Familiarity with software engineering methodologies (agile, scrum) and best practices (CI/CD, code review).
• Strong communication skills, comfortable leading technical discussions and aligning project priorities.

Nice to have

• Experience designing and building microservices, familiar with Kubernetes, Docker, or RESTful API.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of the enterprise SaaS space.

Culture & Benefits

• Work closely with research, engineering, and product partners.
• Opportunity to transform research innovations into real customer impact.
• Collaborative environment with cross-functional teams.