Senior ML Engineer (GenAI)

Provectus

Cali

Presencial

COP 892.800 - 1.116.000

Jornada completa

14 días+

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Descripción de la vacante

A technology company in Cali, Colombia, is looking for a Senior ML Engineer. This position involves designing, developing, and deploying machine learning solutions, optimizing model performance, and mentoring junior engineers. Candidates should have a strong foundation in ML, experience with Python and deep learning, and familiarity with cloud services like AWS. Join us to work on complex ML problems and contribute to innovative solutions in the technology sector. The role offers full-time employment in the dynamic fields of engineering and IT.

Formación

  • Experience in building production LLM-based applications and prompt engineering.
  • Strong understanding of ML fundamentals, model development, and frameworks.
  • Knowledge of cloud-native architectures and infrastructure as code.

Responsabilidades

  • Design and implement end-to-end ML solutions from experimentation to production.
  • Mentor junior and mid-level ML engineers on best practices and code reviews.
  • Optimize model performance, efficiency, and reliability.

Conocimientos

Machine Learning Core
Python
Deep Learning
MLOps
Data Pipelines
Containerization

Herramientas

AWS
Spark
SQL

Descripción del empleo

6 days ago Be among the first 25 applicants

As a Senior ML Engineer at Provectus, you'll be responsible for designing, developing, and deploying production-grade machine learning solutions for our clients. You will work on complex ML problems, mentor junior engineers, and contribute to building ML accelerators and best practices.

Core Responsibilities
  • Technical Delivery (60%): Design and implement end-to-end ML solutions from experimentation to production
  • Build scalable ML pipelines and infrastructure
  • Optimize model performance, efficiency, and reliability
  • Write clean, maintainable, production-quality code
  • Conduct rigorous experimentation and model evaluation
  • Troubleshoot and resolve complex technical challenges
  • Collaboration and Contribution (25%): Mentor junior and mid-level ML engineers
  • Conduct code reviews and provide constructive feedback
  • Share knowledge through documentation, presentations, and workshops
  • Collaborate with cross-functional teams (DevOps, Data Engineering, SAs)
  • Contribute to internal ML practice development
  • Innovation and Growth (15%): Stay current with ML research and emerging technologies
  • Propose improvements to existing solutions and processes
  • Contribute to the development of reusable ML accelerators
  • Participate in technical discussions and architectural decisions
Requirements
  • Machine Learning Core: ML Fundamentals, model development, ML frameworks, deep learning
  • LLMs and Generative AI: experience building production LLM-based applications, prompt engineering, RAG systems, vector databases, LLM evaluation
  • Data and Programming: Python, pandas, numpy, SQL, data pipelines, Spark or similar
  • MLOps and Production: model deployment, containerization, CI/CD, monitoring, experiment tracking
    Cloud and Infrastructure
  • AWS services, GCP expertise, cloud-native architectures, IaC
Will be a plus
  • Practical experience with cloud platforms (AWS stack preferred)
  • Practical experience with deep learning models
  • Experience with taxonomies or ontologies
  • Experience with machine learning pipelines to orchestrate complicated workflows
  • Experience with Spark/Dask, Great Expectations

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.

Seniority Level

Not Applicable

Employment Type

Full-time

Job Function

Engineering and Information Technology

Industries

Transportation, Logistics, Supply Chain and Storage

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