Senior Machine Learning Engineer Jobs in Waterloo, ON

WHAT'S IN IT FOR YOU 

Benefits:

Compensation: $88,000 - $121,000
Annual Performance-Based Incentive Bonus 
5% RRSP match 
Stock purchase plan 
Starting 3 weeks of vacation 
Benefits package (health and dental) + $600 health spending account 
Half-Day Fridays 
Continuous learning and career growth with global mobility opportunities. 
A chance to contribute to something bigger - advancing the future of healthcare through automation. 

QUALIFICATIONS:

Education
•    A post-secondary engineering degree, diploma or equivalent in a quantitative field (Computer Science, Information system, Mathematic, Statistics, Machine Learning, Artificial intelligence, Engineering)
•    A Master’s degree is considered beneficial.

Experience
•    Strong experience with the deployment, configuration, and operationalization of Databricks environments, including workspace architecture, cluster management, CI/CD integration, security, governance, and enterprise-scale administration.
•    Experienced in building and managing modern data pipelines and lakehouse architectures using Delta Lake, Delta Live Tables, Structured Streaming, Workflows, medallion architectures (Bronze/Silver/Gold), and real-time/batch ingestion frameworks.
•    Deep understanding of Databricks ecosystem components including Unity Catalog, data lineage, RBAC, monitoring/observability, cost optimization, ML/AI enablement, model serving, and secure enterprise data collaboration through Clean Rooms. 
•    Proven experience integrating Databricks with enterprise cloud and industrial data ecosystems, including Kafka, SQL databases, APIs, IoT/OT platforms, and cloud environments such as Azure, AWS, and GCP. 
•    Strong understanding of scalable data engineering, governance, multi-tenant architectures, and enterprise data platform strategies supporting analytics, AI, and operational intelligence initiatives.
•    Proficiency in programming languages like Python, R, or Java
•    Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy)
•    Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
•    Experience with databases (SQL, Influx)
•    Knowledge of data warehousing and ETL processes
•    Familiarity with tools like Hadoop, Spark, or Kafka
•    Experience with cloud services such as AWS, Google Cloud, or Azure
•    Understanding of software engineering principles and best practices
•    Experience with version control systems (e.g., Git)
•    Ability to design and implement efficient algorithms and solutions
•    Demonstrated experience in deploying machine learning models to production
•    Experience with data visualization tools and techniques
•    Strong analytical and communication skills
•    Ability to work collaboratively in a team environment
•    Ability to communicate effectively, both orally and in writing
•    A self-starter with the ability to work as part of a team in a fast paced environment with minimal supervision
•    In addition, the following is considered not necessary but beneficial:
o    Experience with Agile development practices
o    Understanding of automation mechanical, electrical and control systems
o    Understanding of machine operation, maintenance, service and troubleshooting
o    Understanding of Machine Vision systems and solutions
o    Understanding of PLCs and PLC communication
o    Exposure and understanding of business intelligence

HEALTH, SAFETY, AND ENVIRONMENTAL: 

•    All employees have the responsibility to work in a safe manner and report any health, safety or environmental concern to their manager or supervisor in a timely manner. 
•    Work in compliance with divisional health, safety and environmental procedures 
•    Refrain from removing or altering safety devices or guarding unless hazardous energies are controlled through lockout-tagout methods 
•    Report any unsafe conditions or unsafe acts • Report defect in any equipment or protective device 
•    Ensure that the required protective equipment is used for the assigned tasks 
•    Attend all required health, safety and environmental training 
•    Report any accidents/incidents to supervisor 
•    Assist in investigating accidents/incidents 
•    Refrain from engaging in any prank, contest, feat of strength, unnecessary running or rough and boisterous conduct