Applied AI Engineer — End-to-End AI for Sustainable Housing

Anoris Dental; Philippines; Remote; PHP 9,428,000 - 15,713,000; Full time

Benefits offered by this job

Equity

Medical, dental & vision plans

401(k) with 4% match

Unlimited PTO

12 weeks parental leave

Home office setup stipend

Cell phone stipend

Team offsites

Job summary

Anori is seeking versatile AI engineers to join our interdisciplinary team building an AI platform from the ground up. You will prototype, benchmark, and deploy end-to-end AI solutions, working with multimodal data and cross-functional collaborators to deliver real user value.

You will contribute from initial prototype to production, tackling regulatory data challenges, designing scalable pipelines, and validating models in a fast-moving early-stage company environment.

Qualifications

• Bachelor's degree in CS or equivalent practical experience.
• 3+ years of experience building and deploying AI systems.
• Experience working with messy and complex real world data sets.
• Strong Python development skills.

Responsibilities

• Develop AI systems for regulatory data to ensure accurate and validated interpretations of nuanced requirements, conditions, and constraints
• Design, prototype, benchmark, validate and implement robust, end to end production-level software to enable inference, optimization, and other complex AI workflows as part of a SaaS offering
• Build scalable, reproducible deployment pipelines for AI services
• Work effectively with cross-functional teams of engineers, scientists, domain experts and PMs

Skills

Python development

Education

Bachelor's degree in CS or equivalent practical experience

Job description

Anori is seeking versatile AI engineers to join our interdisciplinary team building an AI platform from the ground up. You will prototype, benchmark, and deploy end-to-end AI solutions, working with multimodal data and cross-functional collaborators to deliver real user value.

You will contribute from initial prototype to production, tackling regulatory data challenges, designing scalable pipelines, and validating models in a fast-moving early-stage company environment.