Job Overview
Location
Columbia - Bogotá
Job Type
Contract
Category
Software Engineering
Date Posted
May 26, 2026
Full Job Description
📋 Description
- • Design, build, and maintain robust data pipelines for ingestion, transformation, and feature engineering using structured and unstructured data including text, tabular, and time-series formats.
- • Develop, train, evaluate, and iterate on machine learning models for classification, regression, clustering, and NLP tasks using Python and core ML libraries such as scikit-learn, PyTorch, or TensorFlow.
- • Fine-tune and adapt pre-trained LLMs and transformer-based architectures for specific use cases and datasets in production environments.
- • Build and manage MLOps infrastructure including model versioning, experiment tracking, and deployment pipelines using tools like MLflow, Weights & Biases, or DVC.
- • Monitor model performance in production and implement retraining strategies and drift-detection mechanisms to ensure ongoing accuracy and reliability.
- • Collaborate with engineering and product teams to translate data insights into actionable AI features integrated into company products.
- • Document data schemas, model architectures, and pipeline logic thoroughly to ensure maintainability and knowledge sharing across teams.
- • Work with large-scale datasets across data warehouses and lakes such as Snowflake, BigQuery, or Redshift.
- • Utilize LLM platforms including Hugging Face, OpenAI, or Anthropic for model development and deployment.
- • Operate within cloud infrastructure environments on AWS, GCP, or Azure to support scalable ML solutions.
- • Use remote collaboration tools including Slack, Zoom, Google Workspace, and Asana to coordinate with distributed teams across US time zones (EST–PST).
- • Ensure compliance with data quality principles and statistical best practices throughout the machine learning lifecycle.
- • Complete a mandatory video application as the first step in the interview process; applications without a video will not be considered.
🎯 Requirements
- • Strong Python skills with hands-on experience in core ML libraries (scikit-learn, PyTorch, TensorFlow, or similar)
- • Solid data engineering experience — SQL, ETL pipelines, and working with large-scale datasets
- • Practical experience with model training, evaluation, hyperparameter tuning, and deployment
- • Familiarity with LLMs and transformer-based architectures; experience with fine-tuning or prompt engineering in production contexts
- • Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC, or similar)
- • Must have prior remote work experience, be fluent with remote collaboration tools (Slack, Zoom, Google Workspace, Asana), and have ideally worked with US or UK-based companies
🏖️ Benefits
- • Remote work opportunity within US time zones (EST–PST)
- • Work with fast-growing global companies
- • Competitive pay
- • Real growth opportunities
Skills & Technologies
About Hangar Aviation Technologies, Inc.
Provider of an online platform that connects aircraft owners and operators with certified pilots and instructors for on-demand charter, rental, training and ferry flights. The marketplace vets pilots, manages scheduling, payment and insurance, giving owners access to qualified crew while enabling pilots to find work across piston, turboprop and jet aircraft nationwide. Based in Austin, Texas, the company serves private owners, flight schools, charter operators and corporate flight departments seeking flexible pilot staffing solutions.
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