Machine Learning / AI Engineer

Machine Learning / AI Engineer You build and ship machine learning and AI features in production. Some weeks you are building retrieval over a large language model; others you are hardening an inference pipeline. Remote · Latin America · $5,500-$7,000 USD/month · Full-time · Independent Contractor · Monday to Friday · 9 AM-6 PM CT Why this role exists Our client is a funded AI-native startup that builds products on top of machine learning and large language models. They ship real AI features to production and need engineers who can take models from prototype to reliable, scalable systems. What you'll own Machine learning and large language model features: built, trained, fine-tuned or integrated The data and inference pipelines that put models into production Model evaluation, with improvements to accuracy, latency and cost AI features shipped end to end with product and engineering Production monitoring, fixing drift, errors and bottlenecks Staying current with the AI tooling landscape and applying what is useful Why this is interesting Real AI features that reach users, not just prototypes Ownership of models and pipelines in production A funded AI-native startup working with large language models, retrieval and agent systems What we're looking for 3+ years building machine learning or AI systems, with work that reached production Strong in Python and the modern AI stack (large language model APIs, retrieval, frameworks such as LangChain, vector databases) Solid grasp of data pipelines, evaluation and the engineering around models, not just notebooks You ship reliable systems and take ownership of what you build English C1, written and spoken. You work comfortably with a US team Bonus Fine-tuning, retrieval-augmented generation or agent systems in production Cloud and MLOps experience (AWS, GCP, containers, pipelines) Degree in computer science, data or a related field What success looks like First 90 days You understand the current ML architecture, data pipelines and production models. You have shipped one feature or hardened one pipeline end to end, and you are trusted to own a model or pipeline without constant review. Ongoing You regularly ship AI features that improve the product and reach users. Models you own stay reliable in production with minimal drift or errors, and you improve accuracy, latency or cost on at least one system per quarter. Why Puente Puente connects experienced Latin American professionals with growing US companies. We do not operate as a generic job board: we selectively match candidates with active roles and guide them through the hiring process. 3% acceptance rate · 2,873+ professionals placed · 97% retention beyond 12 months · 18 countries · 100% remote Hiring process Apply, including a short skills assessment Puente screening: a WhatsApp intro, then a recruiter interview Client interview with the hiring manager Background check and offer Apply now Submit your resume in PDF and complete the short skills assessment we share with every applicant. It is how we evaluate written communication, accuracy and attention to detail for this role.