Remote Machine Learning Engineer Jobs in Argentina

8 Machine Learning Engineer jobs in Argentina available for remote work from home. Apply for positions such as Senior Machine Learning Engineer, Senior Machine Learning Engineer - Argentina, Machine Learning Engineer / Data Scientist (Semi-Senior – Senior) (Remote) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.

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Remote Machine Learning Engineer Jobs in Argentina (8)

Search = Machine Learning Engineer Remote in = Argentina
The role involves working on an intelligent matching project between doctors and pharmaceutical products, requiring technical evolution towards Generative AI and LLMs. Responsibilities include developing and maintaining data pipelines and applying classical Machine Learning techniques.

Machine Learning Engineer Sr.

Flux IT SA · Full Time · 13 Weeks Ago
Flux IT SA
The mission involves designing and executing applied research to validate the use of Machine Learning and Generative AI in real-world scenarios with prospects or clients. This is achieved by creating Proofs of Concept (POCs) to reduce technical uncertainty and establish foundations for productive and commercial initiatives.

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Machine Learning Engineer Ssr.

Flux IT SA · Full Time · 15 Weeks Ago
Flux IT SA
The mission involves designing and executing applied research to validate the use of Machine Learning and Generative AI in real-world scenarios with prospects or clients. This is achieved by creating Proofs of Concept (POCs) to reduce technical uncertainty and establish foundations for productive and commercial initiatives.
R2 is hiring for remote Lead Machine Learning Engineer

Lead Machine Learning Engineer

R2 · Full Time · 18 Weeks Ago
R2
🌎 Argentina, Brazil, Colombia ⭐ 5-10 yrs exp 💼 Software Development Machine Learning Engineer
The Lead Machine Learning Engineer will own the end-to-end lifecycle of machine and deep learning systems in production, defining standards, tooling, and architectural patterns for model deployment, monitoring, retraining, and governance. This role involves architecting, implementing, and deploying ML/DL models while automating monitoring and maintenance systems to ensure model performance and robustness.

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