8 publicaciones de empleo destacadas de stack sr en buenos aires, b (¡Están contratando!)

Senior AI Engineer – GenAI & Agentic Systems
Provectus —Buenos Aires, Buenos Aires
- Tiempo completo
Postulación rápida
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Marvik —Buenos Aires, Buenos Aires
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Stechs —Capital Federal, Buenos Aires
Senior Site Reliability Engineer
Enumerate —Capital Federal, Buenos Aires
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Stechs —Capital Federal, Buenos Aires
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Modus Digital —Capital Federal, Buenos Aires
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Sr Full-Stack Developer
Workana —Buenos Aires, Buenos Aires
- Tiempo completo
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21h
Scribd - Senior SWE (Identity)
Silver.dev —Buenos Aires, Buenos Aires
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Senior AI Engineer – GenAI & Agentic Systems

Provectus -
Buenos Aires, Buenos Aires

Postulación rápida

Detalles del empleo

Tiempo completo
Hace 10 horas

Descripción completa del empleo

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!

Requirements:

Comfortable with standard ML algorithms and underlying math.
Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
AWS Bedrock experience strongly preferred
Practical experience with solving classification and regression tasks in general, feature engineering.
Practical experience with ML models in production.
Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
Python expertise, Docker.
English level - strong upper- intermediate.
Excellent communication and problem-solving skills.

Will be a plus:

Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
Practical experience with deep learning models.
Experience with taxonomies or ontologies.
Practical experience with machine learning pipelines to orchestrate complicated workflows.
Practical experience with Spark/Dask, Great Expectations.

Responsibilities:

Create ML models from scratch or improve existing models.
Collaborate with the engineering team, data scientists, and product managers on production models.
Develop experimentation roadmap.
Set up a reproducible experimentation environment and maintain experimentation pipelines.
Monitor and maintain ML models in production to ensure optimal performance.
Write clear and comprehensive documentation for ML models, processes, and pipelines.
Stay updated with the latest developments in ML and AI and propose innovative solutions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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Senior AI Engineer – GenAI & Agentic Systems

Lead Data Engineer

OSS Solutions EngineerSsr/Sr

Senior Site Reliability Engineer

OSS Solutiones Engineer Ssr

Engineering Technical Lead

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Scribd - Senior SWE (Identity)

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