3.538 Ofertas de Machine Learning en Colombia
Machine Learning
Hoy
Trabajo visto
Descripción Del Trabajo
Our client is the leading airline in Latin America, offering the broadest network of destinations, flight frequencies, and aircraft fleet in the region. The company is driving innovation and quality through advanced AI/ML technologies.
Project overview
The project is in the early discovery phase, with a strong emphasis on GenAI and LLM-based solutions.
Position overview
You will join a strategic initiative focused on enhancing operational safety and predictive capabilities using advanced AI and machine learning. Your role will involve leading the development and deployment of these models, integrating them into scalable, production-ready systems.
Responsibilities
- Lead the design and development of ML/AI-based solutions to address real-world challenges in aviation.
- Ensure scalable and reliable deployment of ML and LLM models in production environments.
- Collaborate with DevOps and SRE teams to define and improve practices tailored to GenAI/LLM solutions.
- Build internal tools to streamline model development, evaluation, and deployment processes.
- Operate and monitor AI/ML platforms and systems, ensuring performance, availability, and rapid response to incidents.
- Contribute to the continuous optimization of CI/CD pipelines and infrastructure.
Requirements
- Experience with Google Cloud Platform (GCP)
- Experience in Python and key ML libraries
- Experience deploying and maintaining ML systems in production
- Familiarity with infrastructure as code tools such as Terraform
- Experience with containerization (Docker) and CI/CD pipelines
- Solid understanding of ML lifecycle, from data preparation to model monitoring
- Experience with ML Ops tools (e.g., Airflow, MLflow)
- Some background in developing and scaling LLMs or GenAI solutions
- Understanding of observability and incident response in AI/ML production environments
Buscamos perfiles Middle, strong Middle y Senior, no es requerido el inglés
Machine Learning
Hoy
Trabajo visto
Descripción Del Trabajo
En Sofka tenemos uno claro: "cuidar nuestro entorno multiplicando experiências exitosas".
¡Alista tu mochila y sé parte de esta gran aventura!
¿Qué buscamos?
Mochileros y Mochileras apasionados por la ingeniería de datos, con gran capacidad para diseñar, producir y crear modelos con el objetivo de tener un gran impacto en el negocio.
Si cuentas con **TRES AÑOS** de experiência desempeñando roles similares, manejando bases de datos relacionales y documentales, librerías estadísticas y de aprendizaje automático, posees conocimientos de programación en Python implementando modelos de aprendizaje de máquinas, y conoces al menos un proveedor de servicios en la nube como AWS, Azure y/o GCP.
Esta es una gran oportunidad
Es un **PLUS** si tienes:
- Formación en áreas de ingeniería (sistemas, electrónico, físico, control, etc), matemáticas y/o estadística.
- Experiência con librerías estadísticas y de aprendizaje automático junto con la capacidad de aplicarlas adecuadamente a problemas comerciales, como: Tensorflow, scikit-learn y/o Pytorch.
- Experiência en procesamiento de lenguaje natural, especialmente en señales y ondas de audio.
- Conocimientos en procesos de CI/CD y desarrollo de pipelines
- Dominio de algún IDE de programación (visual studio code, PyCharm, etc.)
- Conocimientos en lenguajes de programación como R, Scala y/o SAS.
- Manejo de herramientas de versionamiento (git).
- Conocimiento en ambientes de big data como Hive, Hadoop, Impala y/o Spark.
- Nível ingles B en adelante.
¡PRESÉNTATE!Condiciones
- **Contrato a término indefinido**, nos encantan las relaciones a largo plazo por lo que queremos que formes parte de esta familia por mucho tiempo.
- Puedes estar ubicado en **cualquier lugar del mundo**, ¡nos gusta que trabajes de forma remota! Pero si te encuentras en **Medellín** y **Bogotá** queremos que dos días al mes trabajes desde casa Sofka, buscando generar **SINERGÍAS** y **FORTALECER** lazos con tu equipo de trabajo, además que compartas un rico almuerzo. ¿Y por qué no? una bebida para refrescarte. Adicional si quieres ir mas días a la oficina tendrás tu almuerzo reservado para ese día.
- ¿Buscas **crecimiento profesional**? Puedes diseñar tu plan carrera acorde a lo que buscas y te quieres proyectar.
¿Qué encontrarás?
- Somos un equipo conectado con el **crecimiento**.
- Tenemos una **cultura de mejora continua, fresca **y** colaborativa** donde cada día puedes encontrar una oportunidad y lo más importante **personas dispuestas **a apoyarte.
- Encontrarás** retos** técnicos y personales.
- ¡**Saca tu mejor potencial**! con nuestro programa **Bekaizen **donde puedes crecer y desarrollar tus talentos donde será todo un reto y un juego, acompañado de feedback constante por tus líderes, mentorias y coaching por parte de **Sofka U**,
- Más que una empresa encontrarás un **equipo** donde tu **bienestar físico y mental** es importante.
- Contamos con diferentes programas dirigidos a potencializar tus competencias, viviendo diariamente la mejora continua y promoviendo tu bienestar físico y emocional. Se llaman **Kaizen Life** y **WeSofka**, en donde contarás con diferentes beneficios que irás adquiriendo en el tiempo cómo pólizas de salud para ti, tu familia y mascotas, potencializar tu segundo idioma (inglés), ahorro con propósito, gimnasio y más.
Machine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrSé el primero en saberlo
Acerca de lo último Machine learning Empleos en Colombia !
Machine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-LjbffrMachine Learning Engineer
Publicado hace 10 días
Trabajo visto
Descripción Del Trabajo
We are looking for a Machine Learning Engineer with strong expertise in computer vision and object detection to tackle a specialized challenge: detecting walls and identifying rooms in architectural blueprints or pre-construction plans.
This role is ideal for someone who is hands-on, detail-oriented, and passionate about applying advanced ML techniques to solve real-world problems.
Key Responsibilities- Develop and fine-tune ML models for detecting walls in architectural blueprints.
- Design and implement preprocessing pipelines for handling blueprint files (images/PDFs).
- Optimize model inference using ONNX Runtime for production-ready deployment.
- Build and maintain an API server to serve ML inference (preferably using BentoML).
- Collaborate with stakeholders to define requirements, deliver milestones, and document solutions clearly.
- Strong hands-on experience with PyTorch for model development and training.
- Expertise with Ultralytics (YOLOv8) for object detection tasks.
- Proficiency in OpenCV, Pillow (PIL), and NumPy for preprocessing and image manipulation.
- Experience with ONNX / ONNX Runtime for optimized inference.
- Solid knowledge of BentoML (preferred) or FastAPI for serving ML APIs.
- Familiarity with Pydantic for schema validation.
- Proven track record of deploying ML models into production.
- Strong problem-solving mindset and ability to adapt ML tools to specialized use cases.
- Clear communication and documentation skills.
- Experience working with PyMuPDF for parsing PDF-based architectural plans.
- Background in architectural/engineering data or prior work with blueprint analysis.
- Knowledge of clustering/grouping methods for room identification tasks.
- Familiarity with MLOps practices (monitoring, scaling, CI/CD for ML).
Schedule : Monday to Friday - Full-time
Compensation : USD salary
Location : 100% remote
#J-18808-Ljbffr