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Machine Learning Developer Intern Jobs in Waterloo, ON

ATS Automation

Data Scientist

Cambridge, ON · On-site

CA$600/day

Education • A post-secondary engineering degree, diploma or equivalent in a quantitative field (Computer Science, Information system, Mathematic, Statistics, Machine Learning, Artificial ...

Sonova

Senior Software Developer

Kitchener, ON · Hybrid

Kitchener, Ontario - Hybrid Senior Software Developer Join Sonova's Manufacturing Software team and ... machine learning, or data visualization tools such as Apache Superset is a plus Precise, self ...

OFNTSC

Infrastructure Specialist Intern

Brantford, ON · On-site

CA$25 - CA$28/hr

College Diploma in Civil Engineering, Construction Management, Architectural Technology/Technician ... Adaptable and committed to continuous learning, with a solid understanding of technical ...

OFNTSC

Infrastructure Specialist Intern

Brantford, ON · On-site

$25 - $28/hr

College Diploma in Civil Engineering, Construction Management, Architectural Technology/Technician ... Adaptable and committed to continuous learning, with a solid understanding of technical ...

Sun Life Financial

Senior Data Scientist

Waterloo, ON · On-site

Apply best-in-breeddata science techniques including descriptive, predictive, and machine learning methods from design to implementation * Focus on feature engineering, model training, model ...

Syntronic

Lead Software Developer (AOSP)

Waterloo, ON · On-site

CA$140K - CA$170K/yr

We are seeking a Lead Software Engineer to drive the design, development, and maintenance of ... Knowledge of Machine Learning and experience using AI tools in the development process.

Dialpad

Applied Scientist

Kitchener, ON · On-site +1

Collaboration will be key as you work alongside our engineering, design, and product teams to build ... Demonstrated experience with machine learning, Python, PyTorch, and other relevant tools and ...

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All JobsMachine Learning Developer Intern JobsMachine Learning Developer Intern Jobs in Waterloo, ON

Machine Learning Developer Intern information

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a machine learning developer intern?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Waterloo, ON are hiring for Machine Learning Developer Intern jobs?

Cities near Waterloo, ON with the most Machine Learning Developer Intern job openings:

Machine Learning Developer Intern jobs near you

Data Scientist

ATS Automation

Cambridge, ON • On-site

CA$600/day

Full-time

Medical, Dental, PTO

Re-posted 15 days ago

Job description

Data Scientist

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

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

H&S

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

Join our Innovation Center at ATS Corporation - a place to create differentiators with the future in mind. Our Innovation Center is focused on R&D; advancing existing technologies, filling gaps in existing automation products, technologies and processes to give ATS a competitive advantage

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