Machine Learning Advisor

Avoltacanada; Old Toronto; Remote; CAD 60,000 - 80,000; Full time

Job summary

Join an innovative startup as a Machine Learning Advisor, where you'll engage in cutting-edge automotive anti-theft solutions. This role offers a unique opportunity to work alongside a passionate team, contributing to the development of advanced machine learning algorithms that enhance vehicle security. You'll gain hands-on experience in a dynamic environment, collaborating on real-world projects that make a difference. With mentorship from industry experts, this position is perfect for someone eager to grow their skills and make an impact in the field of machine learning and security.

Benefits

Hands-on experience in a startup

Cutting-edge project opportunities

Mentorship from professionals

Networking opportunities

Qualifications

• Enrolled in a relevant program in Computer Science or Machine Learning preferred.
• Solid understanding of machine learning fundamentals and algorithms.

Responsibilities

• Engage with the team to understand machine learning project goals.
• Support data gathering and preprocessing for model training.

Skills

Machine Learning

Python

Data Science

TensorFlow

PyTorch

scikit-learn

Problem Solving

Communication Skills

Education

Bachelor's in Computer Science

Master's in Computer Science

Tools

Microcontrollers

Sensors

Job description

Company: Avolta

Position: Machine Learning Advisor

Location: Remote (Toronto, ON)

About Avolta: Avolta is a cutting-edge startup focused on revolutionizing automotive anti-theft security. Leveraging advanced technologies, we are dedicated to creating innovative solutions that safeguard vehicles from theft and unauthorized access. As a dynamic and fast-paced company, we are seeking a talented Machine Learning advisor to join our team and contribute to our mission.

Position Overview: We are seeking a passionate and motivated Machine Learning advisor to assist our research and development team in advancing our automotive anti-theft security systems.

Responsibilities:

1. Engage with the research and development team to grasp the requisites and goals of machine learning initiatives.
2. Support in gathering, preprocessing, and scrutinizing pertinent data for the training and validation of machine learning models.
3. Design and execute machine learning algorithms tailored for vehicle security and anti-theft implementations.
4. Refine existing machine learning models and explore novel strategies to enhance accuracy and efficacy.
5. Actively participate in ideation sessions, offering inventive suggestions to bolster our security solutions.
6. Document and present your contributions comprehensively, detailing methodologies, discoveries, and potential enhancements.
7. Keep abreast of the latest developments in machine learning and security, enriching the team's knowledge repository with valuable insights.

Qualifications:

• Enrolled in a relevant undergraduate or graduate program in Computer Science, Machine Learning, Data Science, or a related field preferred.
• Solid understanding of machine learning fundamentals and algorithms.
• Proficiency in programming languages such as Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with electronics (e.g. microcontrollers) and sensors preferred.
• Familiarity with data preprocessing techniques and feature engineering.
• Strong problem-solving skills and the ability to work independently as well as collaboratively.
• Excellent communication skills to present findings and ideas effectively.
• Prior projects or coursework related to machine learning, computer vision, or security is a plus.
• A bachelor's or master's degree in computer science, engineering, mathematics, or a related field, with a focus on machine learning, artificial intelligence, or cybersecurity, is typically required. Advanced degrees or relevant certifications are a plus.

Benefits:

• Hands-on experience in a dynamic startup environment.
• Opportunity to work on cutting-edge machine learning projects with real-world impact.
• Mentorship and guidance from experienced professionals in the field.
• Networking opportunities with fellow industry experts and student interns.

The compensation for this advisory role would be pro-bono (unpaid).