VRIFY is positioned at the forefront of the mining industry's transformation, leveraging cutting-edge AI to revolutionize mineral exploration. With a focus on AI drill targeting, VRIFY is expanding its capabilities by synthesizing vast amounts of geological information. This integration enhances the precision and efficiency of exploration strategies, offering our clients innovative solutions that depart from traditional methods.
Our mission extends beyond technological advancement. We are committed to transforming how mining companies engage with investors, aiming to foster a more transparent and accountable mining investment ecosystem. VRIFY's technology enables immersive 3D and 360° presentations that provide investors with a vivid and detailed visual context, making complex geological data accessible and engaging.
As we continue to refine our AI-driven solutions, VRIFY remains dedicated to driving innovation and excellence in the mining sector, ensuring our clients and investors are well-equipped to succeed in a rapidly evolving market.
About the Role:
As the Senior Developer - Machine Learning Operations, you will be at the forefront of developing and optimizing our machine learning operations platform, a critical component in deploying, managing, and scaling our machine learning models in production.
In this role, you will design, implement, and streamline automated pipelines for model training, validation, deployment, monitoring, and evaluation. You will manage the entire lifecycle of machine learning models, from experimentation to production, ensuring adherence to best practices in version control, testing, and CI/CD.
The ideal candidate possesses a deep understanding of MLOps, cloud-based machine learning platforms, and automation frameworks. You will also play a key role in mentoring and guiding other developers, fostering a culture of continuous improvement, technical excellence, and innovation in machine learning operations.
Key Responsibilities:
- Develop and maintain automated pipelines for model training, validation, deployment, monitoring, and evaluation, ensuring seamless integration into production environments.
- Oversee the deployment of machine learning models to production, ensuring they are scalable, reliable, and optimized for performance across different environments.
- Set up robust monitoring systems to track model performance and data drift in production, and establish processes for regular model updates and maintenance.
- Design and optimize cloud infrastructure to support the entire machine learning lifecycle, from data ingestion and processing to model training and deployment.
- Establish and enforce best practices for model lifecycle management, including reproducibility, scalability, security, and compliance with industry standards.
- Stay updated on the latest advancements in MLOps tools, techniques, and frameworks, and lead the integration of new tools and technologies to improve the platform’s capabilities.
- Work closely with data scientists, software developers, geologists and product managers to translate complex machine learning models into scalable, production-ready solutions.
Qualifications:
- BSc, MSc, PhD in Computer Science, Engineering or a related field, or equivalent practical experience in ML engineering or MLOps role
- 2+ years of direct relevant experience in MLOps, including experience operating a machine learning system in a production environment
- 3+ years experience with any of popular machine learning frameworks: Pytorch, Pytorch lightning, Tensorflow, Jax, scikit-learn
- Deep understanding of popular machine learning architectures, such as transformer and vision transformer, and strategies like decision forests and clustering
- 6+ years of experience in software development in at least one high-level programming language like Python, Go, Java
What We Offer:
- Health Benefits: Extensive coverage, medical, dental, and vision plans.
- Paid Time Off (PTO): Including vacation days, sick days, personal days, public holidays plus extra time during holiday season.
- Work-Life Balance: Flexible work hours, remote work options plus option to use work space in Downtown Vancouver (free snacks & gym).
- Professional Development: Career growth program to help our team unlock their potential and advance their career.
- Performance Bonuses
- Wellness Programs: Fitness allowance, work from home allowance, mental health support.
- Retirement Plan (RRSP/DPSP)
This job description has been written to provide an accurate reflection of the current job and to include the general nature of work performed. It is not designed to contain a comprehensive detailed inventory of all duties, responsibilities, and qualifications required of the employees assigned to the job. Management reserves the right to revise the job or require that other or different tasks be performed when circumstances change.
We strive to create an environment where every employee feels valued, respected, and empowered regardless of their race, gender, age, religion, identity, or experience. We understand that unique perspectives and backgrounds bring invaluable insights and contribute to the richness of our culture and the effectiveness of our solutions. If you have a disability or any special needs that we might need to accommodate, please let us know.
