Senior ML/AI Engineer

Provectus; Bogotá; Presencial; COP 112.566.000 - 187.611.000; Jornada completa

Descripción de la vacante

A technology consultant in Bogotá is seeking a skilled ML Engineer to develop and improve machine learning models. The ideal candidate will have solid software engineering skills, experience in ML production environments, and expertise in Python and Docker. Strong knowledge of standard ML algorithms is required. This role offers the chance to work on impactful AI transformations across industries, fostering collaboration within a cross-functional team.

Formación

• Comfortable with standard ML algorithms and underlying math.
• Practical experience with solving classification and regression tasks.
• Experience with ML models in production.

Responsabilidades

• Create ML models from scratch or improve existing models.
• Collaborate with the engineering team and data scientists.
• Monitor and maintain ML models in production.

Conocimientos

Standard ML algorithms

Classification and regression tasks

Monitoring metrics

NLP

LLMs

Recommendation engines

Software engineering skills

Python

Docker

AWS stack

Descripción del empleo

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.

With offices in North America, LATAM, and EMEA, Provectus partners with clients around the world and is obsessed with leveraging cloud, data, and AI to reimagine the way clients operate & compete.

Responsibilities

• Create ML models from scratch or improve existing models.
• Create ML/AI pipelines that include custom models or APIs as part of the processing.
• 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.

Requirements

• Comfortable with standard ML algorithms and underlying math.
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production: orchestrating workflows, monitoring metrics.
• 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.
• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECS, EMR/Glue, S3, Lambda, SQS).
• English level - Upper Intermediate.
• Excellent communication and problem-solving skills.

Will be a plus

• Experience with RAG.
• Experience with taxonomies or ontologies.
• Practical experience with Spark/Dask, Great Expectations.