Ai/Ml Engineer

TL;DR

Ai/Ml Engineer (AI Engineering): Build intelligent AI-powered systems and applications leveraging large language models and data ecosystems with an accent on prototyping AI agents, collaborating with enterprise customers, and developing clean Python code. Focus on designing, benchmarking, and refining AI solutions, integrating structured data and automation, and working in a hybrid environment.

Location: Hybrid role in Redwood City, CA office, local candidates only, no relocation, no visa sponsorship

Salary: $120,576 - $162,778

Company

hirify.global pioneers AI-powered data intelligence, enabling enterprises to drive analytics, cloud transformation, data governance, and AI innovation with a strong customer base including 40% of the Fortune 100.

What you will do

• Prototype AI agents using modern LLM and agent frameworks, evaluating and refining performance.
• Collaborate with technical stakeholders to co-design practical AI solutions for real-world use cases.
• Develop AI-powered applications combining structured data, language models, and automation.
• Write clean, production-quality Python code for integrations and intelligent systems.
• Work closely with product and platform teams to share deployment insights and improve AI platforms.
• Create reusable tools and templates to accelerate future AI implementations.

Requirements

• Local candidates only in Redwood City, CA; no relocation or visa sponsorship
• 1-3 years experience in startups or fast-growing businesses.
• B.S. in Computer Science or related field; M.S. preferred.
• Strong Python skills and familiarity with LLMs or AI system development.
• Comfort with SQL and relational data; knowledge of Snowflake, BigQuery, or Redshift is a plus.
• Clear communication and collaboration skills with technical and non-technical teams.

Nice to have

• Experience deploying AI/ML systems in production with observability and monitoring.
• Background in forward deployed engineering, solutions engineering, or AI consulting.
• Familiarity with data infrastructure, MLOps concepts, APIs, orchestration, containerization, and cloud environments.
• Understanding of enterprise data governance and access control principles.

Culture & Benefits

• Hybrid work model with in-office collaboration on Tuesdays and Thursdays.
• Opportunity to work on cutting-edge AI-powered data intelligence products.
• Collaborative team environment focused on learning and growth.