Senior Full-Stack Engineer: ML Infra (Remote)

AI Acquisition; Philippines; On-site; PHP 3,399,382 - 6,798,765; Full time

Job summary

AI Acquisition is seeking a Senior Technical Developer (Contract) to own the technical and systems layer of an enterprise project controls platform. You will work directly with the founder in a production codebase, building full-stack features and ML/AI pipelines in a fast-paced, no-ticket-theater environment.

Remote work with EST/CST time zones, 25–40 hours per week, and compensation details open. You will own data-heavy pipelines, SQL schemas, and deployment of features across the stack.

Qualifications

• 3+ years of production experience with TS/JS, including generics and type inference.
• Production React experience with ownership of live apps.
• Next.js App Router literacy (server vs client, middleware, route handlers).
• SQL fluency with raw PostgreSQL; no ORM.
• Python for ML data prep, training, and evaluation.
• Strict Git workflow discipline and code reviews.
• Familiarity with ML infrastructure frameworks and fine-tuning experiments.

Responsibilities

• Own building and deployment of full-stack system features.
• Design, implement, and submit PRs for review.
• Build ML pipelines for training, evaluation, and data prep.
• Write complex SQL migrations and data schemas.
• Develop voice pipelines (STT/TTS) and model inference steps.
• Troubleshoot production bugs in a live system.

Skills

TypeScript/JavaScript

React

Next.js App Router

SQL (PostgreSQL)

Python

Git

ML infrastructure familiarity

Strong English writing

Tools

Docker

CI/CD

Job description

AI Acquisition is seeking a Senior Technical Developer (Contract) to own the technical and systems layer of an enterprise project controls platform. You will work directly with the founder in a production codebase, building full-stack features and ML/AI pipelines in a fast-paced, no-ticket-theater environment.

Remote work with EST/CST time zones, 25–40 hours per week, and compensation details open. You will own data-heavy pipelines, SQL schemas, and deployment of features across the stack.