Machine Learning Engineer

About the role

We are seeking a versatile Machine Learning Engineer to help build and scale our AI/ML initiatives from the ground up. In this role, you won't just be handed clean datasets to train models in a vacuum; you will own the entire lifecycle. You will design custom computer vision architectures, build the robust AWS cloud infrastructure to support them, and develop the full-stack interfaces that deliver actionable insights to end-users.

If you are passionate about applying AI to real-world physical challenges—such as environmental sustainability and monitoring—and love the satisfaction of taking a model from a raw TensorFlow graph all the way to a production web application, this role is for you.

What you'll be doing

• Computer Vision Engineering: Train, fine-tune, and deploy custom object detection and classification models.
• Pipeline Architecture: Design efficient edge-to-cloud ingestion pipelines optimized for periodic camera view monitoring (processing high-res image refreshes on a 5-minute basis, rather than handling continuous live video streams).
• AWS Cloud Infrastructure: Build and maintain scalable, automated MLOps pipelines using AWS services (SageMaker, S3, Lambda, ECS/EKS, API Gateway) managed via Infrastructure as Code (Terraform or CDK).
• Full-Stack Development: Develop robust backend APIs (FastAPI/Node.js) and intuitive frontend dashboards (React/Vue) to serve model inferences, manage internal data annotation workflows, and display real-time performance metrics.
• Data Wrangling & Debugging: Master complex data transformations and dimensional debugging—if an array's shape needs to be (3,3,2) instead of (3,2), you know exactly how to reshape and validate it without breaking the pipeline.

What We’re Looking For

• Experience: 5+ years in software engineering, with at least 3 years dedicated to machine learning and computer vision in a production environment.
• ML Frameworks: Deep expertise in Python and major deep learning frameworks (TensorFlow, PyTorch).
• Cloud Native: Proven track record of deploying and orchestrating ML models on AWS, including managing CI/CD pipelines, model registries, and handling data drift.
• Systems Thinker: Ability to balance algorithmic complexity with cloud compute costs, network bandwidth limits, and system latency.
• Full-Stack Proficiency: Comfort working across the stack, from writing SQL queries and optimizing database performance to tweaking UI components for end-user applications.
• Credentials: A Master's or Bachelor's degree in Electrical Engineering, Computer Science, or a related technical field is preferred. P.Eng or PMP certifications are a strong asset for managing complex technical project delivery.

Benefits

Our full-time employees enjoy a range of benefits that support work-life balance, health, and long-term success. This includes:

• Paid time off and holidays
• Employee Assistance Program
• Paid parental leave
• Pension
• Employer-paid medical, dental, vision

Innovasea is an equal-opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.