Senior ML Engineer (AI)

Location: Argentina; 100% remote

Company

hirify.global is a product design, engineering, and marketing firm building custom AI, web, and mobile applications for established brands and funded startups.

What you will do

• Architect and build classical machine learning and generative AI features, including LLM applications, predictive analytics, and agentic workflows.
• Design evaluation frameworks to measure AI quality, reliability, safety, retrieval performance, and business impact.
• Integrate and deploy AI capabilities into client web and mobile applications through APIs and serverless AWS architectures.
• Optimize prompts, system instructions, chunking strategies, accuracy, latency, token consumption, and data privacy.
• Process client data and train or fine-tune algorithms for forecasting, classification, and anomaly detection.
• Participate in client discovery sessions, translate business requirements into technical scopes, demonstrate prototypes, and contribute to code reviews and internal AI runbooks.

Requirements

• 3+ years of software engineering experience focused on machine learning and natural language processing.
• Strong knowledge of LLM architectures, context windows, semantic search, generative AI limitations, and deterministic alternatives.
• Production experience with monitoring, evaluation, debugging, and iterative improvement of AI systems.
• Exceptional Python and SQL skills, including data querying, cleaning, and structuring.
• Hands-on cloud deployment experience, preferably with AWS, plus experience with vector databases and retrieval or agentic frameworks.
• Fluent written and spoken English required; bachelor’s or master’s degree in a relevant field or equivalent practical experience.

Culture & Benefits

• Remote work with a collaborative engineering culture.
• 20 days of paid vacation annually during the first three years, increasing to 25 days later.
• Paid sick leave, 10 national holidays, and 2 company days off.
• Well-being budget, health insurance allowance, and maternity or paternity leave.
• Professional development course and certification reimbursement, hardware based on business needs, and a close-knit team environment.

Hiring process

• Short HR interview.
• Technical interview with an ML Engineer and optionally the CTO, followed by a live-coding interview.
• Offer after successful completion of the interviews.