Machine Learning Engineer

Position Overview

Apera AI is seeking a Machine Learning Engineer to build and enhance the tools, infrastructure, and pipelines that power our AI model training. This role is critical for improving our synthetic data pipeline, automating training evaluations, and developing systems that link data quality to model performance. You will collaborate closely with technical artists, applied scientists, and simulation developers to deliver scalable, production-grade systems for robust AI deployment.

About Apera AI

Apera AI is an innovative, Vancouver-based startup at the forefront of robotics, AI, and machine vision technologies. Backed by VC funding and recognized as a 2024 BCTIA Growth Award winner, we are on a mission to redefine the future of AI-driven robotic vision systems. Our software provides robots with "4D Vision," enabling them to see and handle objects with human-like capability, thereby making factories more flexible and productive. Challenging applications such as bin picking, sorting, packaging, and assembly are now open to fast, precise, and reliable automation. Apera is led by an experienced team from high-growth companies focused on robotics, artificial intelligence, and advanced manufacturing.

Employee Value Proposition (EVP)

• Purpose: Your work will directly influence the precision, speed, and robustness of robotic systems operating on factory floors by improving the data AI models learn from.
• Growth: Develop deep technical skills in computer vision, machine learning, simulation, and experimentation. Gain experience connecting training data to model outcomes and applying state-of-the-art techniques.
• Motivators: Take full ownership of the connection between synthetic data and model performance. Your ideas and tools will shape how we train production-grade AI models and scale to new use cases.

Major Objectives

• Identify and Advance Opportunities in the Data Generation Pipeline: Improve the synthetic data pipeline to increase dataset quality, control, or scalability.
• Design, Test, and Validate New Data-Centric ML Techniques: Propose and implement new data-generation or augmentation techniques based on model bottlenecks, training patterns, or failure modes, validating their effectiveness through training experiments.
• Collaborate Across Disciplines to Deliver Data-Driven Improvements: Partner with ML scientists and technical artists to translate needs into robust software, identifying and addressing gaps in configuration, data realism, and augmentation strategy to improve the overall vision model training process.

Critical Subtasks

• Design and implement tooling to configure and control synthetic data generation at scale.
• Design new data generation strategies to improve model generalization through variation, realism, or structure.
• Run targeted training experiments to measure the impact of data approaches and guide future improvements.
• Build internal tools to expose dataset properties, track changes, and help others reason about training inputs.

Culture and Situation Fit

At Apera AI, we value initiative, clarity, and technical depth. This role is for someone who sees data as a critical component of AI model performance and is driven to optimize it.

Requirements

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Responsibilities

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Application Instructions

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Company Information

• Location: Vancouver, BC
• Industry: Robotics, AI, Machine Vision
• Funding: VC Funded
• Awards: 2024 BCTIA Growth Award Winner