Machine Learning Resident - Client: Blackline Safety (12 months)

“Join us for a unique ML Resident role tackling a time-series problem for workplace safety with ML/DL. You’ll collaborate with a dynamic and fast-paced team of machine learning scientists and domain experts, developing innovative models and products within the energy sector while making a tangible impact on worker safety.”

- Maithrreye Srinivasan, Machine Learning Scientist and Dave Staszak, Lead Machine Learning Scientist

About the Role

This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client afterwards (note: at the discretion of the client). The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities.

About our Client

Blackline Safety is a global leader in connected safety solutions. They develop and manufacture wearable safety technology and cloud-based software that help protect and empower workforces operating in high-risk and remote environments. Their real-time monitoring, data analytics, and gas detection solutions enable organizations to proactively manage worker safety and respond instantly to incidents—ensuring employees stay safe and supported wherever they are. Driven by a commitment to innovation, Blackline Safety combines cutting-edge hardware with advanced software to help clients worldwide keep their teams connected, productive, and confident on the job.

About the Project

To advance workplace safety, Blackline Safety is looking to apply machine learning (ML) models to predict workplace risks, with a focus on forecasting the probability of future gas exposures as a critical risk factor. This initiative is designed to significantly enhance workplace safety and reduce risks for clients.

Blackline Safety’s forward-thinking strategy focuses on identifying, evaluating, and addressing potential risks before they escalate. By utilizing historical and real-time data, technology, and analytical tools, this approach allows organizations to predict and mitigate risks effectively. The benefits include preventing workplace accidents, reducing occupational hazards, and achieving significant cost savings. Moreover, it promotes a secure work environment, which enhances employee well-being and productivity, ultimately contributing to the overall success and safety of the organization.

The ML model will be trained on sensor data, including detailed time-series records of gas exposures, events, bumps and calibrations, and usage. By uncovering patterns that drive operational risks, the model will provide actionable insights to improve safety across all levels of operations.

Required Skills / Expertise

We’re looking for a talented and enthusiastic individual with solid knowledge of machine learning and experience working with time series data.

Key Responsibilities:

• Clean, preprocess, and curate historical datasets.
• Conduct exploratory data analysis to identify patterns and anomalies.
• Design, build, train, and evaluate ML/DL models.
• Collaborate with cross-functional teams to develop minimum viable products (MVPs) and client-centric solutions.
• Engage in regular client meetings, contributing to presentations and reports on project progress.
• Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities.

Required Qualifications:

• Completion of a graduate level program or higher (M.Sc/Ph.D) in Computing Science, ML or Engineering.
• Research or project experience working with time series data and classical time series models (ARIMA, Facebook Prophet, etc.).
• Solid understanding and experience in applications of deep learning techniques like RNNs, LSTMs, GRUs, etc.
• Proficient in Python programming language and related ML frameworks, libraries, and toolkits (e.g., Scikit-learn, TensorFlow, PyTorch, Pandas).
• A positive attitude towards learning and understanding a new applied domain.
• Must be legally eligible to work in Canada.

Preferred Qualifications:

• Publication record in peer-reviewed academic conferences or relevant journals in machine learning.
• Familiarity with time series classification or anatomy detection methods.
• Experience/familiarity with software engineering best practices.

Non-Technical Requirements:

• Desire to take ownership of a problem and demonstrated leadership skills.
• Interdisciplinary team player enthusiastic about working together to achieve excellence.
• Capable of critical and independent thought.
• Able to communicate technical concepts clearly and advise on the application of machine intelligence.
• Intellectual curiosity and the desire to learn new things, techniques, and technologies.

Why You Should Apply

Besides gaining industry experience, additional perks include:

• Work under the mentorship of an Amii Fellow and Amii Scientist for the duration of the project.
• Participate in professional development activities.
• Gain access to the Amii community and events.
• Build your professional network.
• The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion).

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait for the closing April 28, 2025 to apply - we’re excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won’t be used in the selection process.