Senior Machine Learning Engineer – AI Generation Engine

SandboxAQ

Senior Machine Learning Engineer on AI Generation Engine team designing and building AI-first products at SandboxAQ. Focus on the end-to-end ML lifecycle from data exploration to model deployment.

Posted 5/27/2026full-timeRemote • 🇨🇦 CanadaSenior💰 CA$119,000 - CA$210,000 per yearWebsite

Tech Stack

Tools & technologies

NumpyPandasPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks.
Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives.
Contribute to the efforts in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy.
Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context.
Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps.
Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment.

Requirements

What you’ll need

BS in Software Engineering, Computer Science, or equivalent field of study
5+ years of postgraduate experience in software development
Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines.
Strong expertise in Python (including the ML stack: PyTorch, TensorFlow, JAX, NumPy, Pandas)
Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothesis testing to architecture, model training, evaluation, and production deployment.
Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and datasets.

Benefits

Comp & perks

Competitive salary, equity and annual bonus
401k matching at 50% up to IRS maximum contribution
Unlimited PTO plus a summer and winter break (one week each)
Twelve weeks of fully paid parental leave in the US, with another 8 weeks for birthing parents
$750 equipment, software, and office furniture budget
$100 per month for wellness (physical or mental) and $100 for home office bills
Top-notch medical, dental and vision insurance for you and your dependents with all premiums covered at 95% for employees
Family Planning support (fertility, surrogacy, adoption) through Carrot

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data pipelinesmachine learning modelshyper-parameter tuningmodel architecture optimizationdata cleaningfeature engineeringPythonMLOpsCI/CDautomated testing

Soft Skills

collaborationcommunicationproblem-solvinganalytical thinkingattention to detail