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Machine Learning Engineer Part Time Jobs in Waterloo, ON

Dishwasher

Waterloo, ON · On-site

CA$18.08/hr

This is Permanent Part-Time position with 50 hours bi-weekly Schedule Rotation Week 1: * Sun Off ... Continuous learning and growth so you have the skillset needed to succeed and take on new ...

Dishwasher

Waterloo, ON · On-site

CA$18.08/hr

This is Permanent Part-Time position with 50 hours bi-weekly Schedule Rotation Week 1: * Sun Off ... Continuous learning and growth so you have the skillset needed to succeed and take on new ...

Overview Canna Cabana is actively seeking Part-Time Sales Associates at Highland Rd store; who are ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Canna Cabana is actively seeking Part-Time Sales Associates at Highland Rd store; who are ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Machine Learning Engineer Part Time information

How do part-time Machine Learning Engineers typically balance project ownership with limited working hours?

Part-time Machine Learning Engineers often focus on well-defined project segments, collaborating closely with full-time team members to ensure alignment and continuity. Clear communication, thorough documentation, and regular check-ins are key to maintaining progress and integrating their contributions seamlessly. While they may not own entire projects, they often take responsibility for specific modules, models, or experiments, and their schedules are usually coordinated to overlap with team meetings or sprints. This structure allows part-time engineers to add significant value while maintaining a manageable workload.

What is the difference between Machine Learning Engineer Part Time vs Data Scientist Part Time?

AspectMachine Learning Engineer Part TimeData Scientist Part Time
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related; experience with data analysis
Work EnvironmentTech companies, startups, research labs; project-basedBusiness, finance, healthcare; data analysis and reporting
Employer & Industry UsageTech firms, AI startups, R&D departmentsCorporate sectors, consulting firms, research institutions

Machine Learning Engineer Part Time focuses on developing and deploying ML models, while Data Scientist Part Time emphasizes analyzing data to extract insights. Both roles often require similar educational backgrounds and may work in overlapping industries, but their core responsibilities differ. Understanding these distinctions helps job seekers target the right position based on their skills and career goals.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Part Time, and why are they important?

To thrive as a Machine Learning Engineer Part Time, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and ideally a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and cloud platforms, as well as experience with version control systems like Git, is typically required. Excellent problem-solving abilities, adaptability, and clear communication are valuable soft skills for collaborating on projects and conveying technical concepts. These skills ensure effective development, deployment, and optimization of machine learning models within the constraints of a part-time role.

What is a Machine Learning Engineer (Part Time)?

A Machine Learning Engineer (Part Time) is a professional who designs, builds, and implements machine learning models and algorithms, but works fewer hours than a full-time employee—often on a flexible or project-based schedule. These engineers collaborate with data scientists and software developers to integrate intelligent systems into products or services. Part-time roles are ideal for those seeking work-life balance, students, or professionals supplementing their income. Responsibilities may include data preprocessing, model training, and deployment, but the scope is typically tailored to fit part-time hours.
What are the most commonly searched types of Machine Learning Engineer jobs in Waterloo, ON? The most popular types of Machine Learning Engineer jobs in Waterloo, ON are:

Part time Weekend CNC Operator

Liberty Staffing

Cambridge, ON • On-site

Part-time

This job post has expired today. Applications are no longer accepted.


Job description

Current openings for - Friday and Saturday nights 10pm-6am - Saturday and Sunday 8am-8pm - Saturday and Sunday 10am-10pm This Company is a leader in advanced manufacturing, specializing in rapid prototyping, short-run production, and turn-key applications for ultra-precision industries including aerospace, medical, motorsports, green energy, and consumer electronics. This role focuses on machine operation, setup, and maintenance in a high-tech environment dedicated to quality and efficiency. No CAD/CAM programming is required for this position. Key Responsibilities: - Operate CNC machines, including setup, loading parts, verifying settings, and running programs to produce precision components. - Maintain CNC machines according to established procedures to ensure optimal performance. - Read and interpret blueprints, job specifications, and technical drawings. - Troubleshoot and resolve issues during machining operations. - Collaborate with the team to meet production deadlines in a fast-paced environment. Required Abilities and Qualifications: - Proficiency in operating CNC machines with focus on 5- axis machining techniques. - Experience with Heidenhain control systems (mandatory, as machines like the GFMS Mikron MILL X 400 U utilize this). - Competence in reading blueprints and technical drawings to meet ultra-precision requirements. - Ability to work flexible Shifts, including afternoons, nights. and weekends. - Previous experience in precisian manufacturing ind Accommodations are available upon request for all individuals with disabilities taking part in the recruitment and selection process.