Chile Based, Machine Learning Engineer

About the role

Blissway develops technology to modernize toll collection and improve highway safety through a combination of deep tech, AI, hardware, and IoT. We are seeking an engineer to manage the full lifecycle of machine learning models, from raw data collection to production deployment on roadside hardware.

Key facts

What you'll do

• Manage the entire machine learning pipeline, including dataset curation, training, deployment, and monitoring.
• Deploy models to edge devices on actual highway infrastructure.
• Process 11 million images daily to perform detection, segmentation, classification, and re-identification.
• Select and implement appropriate computer vision techniques, ranging from classical algorithms to custom state-of-the-art models.
• Optimize models for speed and power efficiency on roadside hardware.

Requirements

• 2 to 6 years of software engineering experience with a focus on machine learning or computer vision.
• Proven ability to take models from raw data through to production and maintenance.
• Strong software engineering fundamentals with the ability to write production-quality code.
• Deep understanding of modern computer vision and the judgment to choose between simple filters and complex models.
• Willingness to work an average of 55 hours per week, with occasional bursts of 70+ hours for major releases.
• Adaptability to work across different team functions as needed.

Skills & tools

• Python
• TypeScript
• Computer vision (detection, segmentation, classification, embeddings)
• Cloud and edge deployment

Practical notes

• This is an on-site role in Denver, and a relocation bonus is provided.
• The hiring process occurs in cohorts; applications are collected over a two-week window before review begins.
• Benefits include 401(k) matching up to 4%, personalized health coverage via ICHRA, 4 weeks of untracked PTO, 12 weeks of paid parental leave, and a 12-week paid sabbatical every 5 years.
• Equity includes a 24-month exercise window and annual opportunities to sell vested shares.