2.810 Ofertas de Ingenieros de Ia en Colombia

En
Grupo Fractalia
, multinacional con presencia en 12 países y más de 2.000 colaboradores, buscamos un/a
Especialista Senior en Inteligencia Artificial y Machine Learning
para liderar el diseño, desarrollo y puesta en producción de soluciones avanzadas de IA.

La persona seleccionada tendrá un rol estratégico en la implementación de modelos de
ML, NLP e IA generativa
, asegurando su escalabilidad, calidad y alineación con los objetivos del negocio.

Responsabilidades principales:

• Diseñar, desarrollar e implementar soluciones con
  modelos avanzados de ML, NLP e IA generativa
  .
• Analizar casos de uso definidos por el Comité de Transformación IA y traducirlos en soluciones aplicables.
• Supervisar la adquisición, limpieza y preparación de datos, asegurando su calidad e integridad.
• Establecer y mantener
  flujos MLOps
  robustos, eficientes y escalables.
• Gestionar la relación con proveedores externos de desarrollo IA.
• Monitorear y optimizar modelos desplegados en producción, resolviendo incidencias técnicas.
• Documentar arquitecturas, procesos y flujos para asegurar escalabilidad y transferencia de conocimiento.

Requisitos del perfil:

• Formación
  : Grado en Ingeniería Informática, Ciencia de Datos, IA, Matemáticas, Estadística o afines.
• Valorable
  : Máster o especialización en Data Science, IA o Machine Learning.
• Experiencia
  :
• Mínimo
  5 años
  en proyectos de IA/ML/NLP o Data Engineering.
• Diseño e implementación de arquitecturas complejas de IA generativa y NLP.
• Gestión técnica de proyectos y trabajo con proveedores externos.
• Experiencia en metodologías
  Agile
  y equipos multidisciplinares.

Conocimientos técnicos clave:

• Dominio de
  Python
  y librerías: TensorFlow, PyTorch, Hugging Face, LangChain/LangGraph.
• Experiencia en
  RAG, fine-tuning de LLMs, prompt engineering
  y workflows agentic.
• MLOps y despliegue en
  Azure, AWS o GCP
  .
• Manejo experto en
  SQL/NoSQL, data lakes y Big Data
  (Spark, Kafka).
• Contenedores y orquestación con
  Docker y Kubernetes
  .
• Análisis estadístico y tratamiento avanzado de datos.

Ofrecemos:

• Participar en proyectos de
  IA de alto impacto
  dentro de una multinacional tecnológica.
• Entorno de trabajo dinámico, innovador y multicultural.
• Modalidad de trabajo híbrida.
• Oportunidades de formación y desarrollo profesional continuo.

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

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.

• 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

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.

• 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

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.

• 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

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.

• 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

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.

• 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

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.

• 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

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.

• 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