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

• Design and build classical machine learning and generative AI features, balancing agentic architectures with deterministic pipelines.
• Develop evaluation frameworks for AI quality, reliability, safety, and business impact.
• Integrate AI capabilities into client web and mobile applications through AWS serverless services and APIs.
• Optimize prompts, system instructions, chunking strategies, accuracy, latency, token usage, and data privacy.
• Process client data and train or fine-tune predictive models for forecasting, classification, and anomaly detection.
• Lead discovery sessions, translate business requirements into technical scopes, present prototypes, and maintain engineering documentation.

Requirements

• 3+ years of software engineering experience focused on machine learning and natural language processing.
• Strong understanding 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.
• Experience deploying ML or API services in cloud environments, preferably AWS.
• Fluent written and spoken English, with the ability to communicate with client stakeholders.

Nice to have

• Experience with Anthropic Claude, OpenAI, AWS Bedrock, or open-source LLMs.
• Experience with LangChain, LangGraph, LlamaIndex, or equivalent orchestration frameworks.
• Experience with Pinecone, pgvector, Milvus, Qdrant, or other vector databases.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Culture & Benefits

• 20 days of annual paid vacation during the first three years, increasing to 25 days later.
• Paid sick leave, 10 national holidays, and two company days off.
• Well-being budget and health insurance allowance.
• Maternity and paternity leave.
• Professional development course and certification reimbursement, hardware based on business needs, and a collaborative engineering culture.

Hiring process

• HR interview.
• Technical interview with an ML Engineer and CTO, followed by a live-coding interview.
• Offer after the interview stages.