Position: Machine Learning Advisor (Voluntary, Unpaid)
Location: Remote
Commitment: Flexible

About Avolta:
Avolta is a forward-thinking startup dedicated to advancing automotive anti-theft security through innovative technologies. As we continue to develop cutting-edge solutions, we are seeking an experienced Machine Learning Advisor to provide valuable guidance to our research and development team. This is an ideal opportunity for someone who wants to contribute their expertise while benefiting from collaboration and growth in a dynamic and forward-thinking environment.

Position Overview:
This voluntary advisory role is designed to provide you with a platform to sharpen your expertise, expand your network, and engage in innovative projects without the pressure of day-to-day commitments. As a Machine Learning Advisor, you will have the chance to influence real-world applications in automotive security, collaborate with emerging talent, and gain insights into the latest advancements in machine learning and computer vision. Your role will focus primarily on guiding and mentoring, allowing you to contribute your knowledge while enhancing your own skills in leadership and project oversight.

Benefits for You:

• Leadership Development: You’ll gain experience in a mentorship and advisory role, guiding junior team members and interns as they work on real-world projects in machine learning and computer vision.
• Network Expansion: This role offers you the opportunity to build connections with professionals, engineers, and innovators in the fields of machine learning, computer vision, and automotive technology.
• Hands-on Influence: You will shape key decisions in a cutting-edge startup environment, contributing to important advancements in vehicle security technology, which will add significant weight to your professional portfolio.
• Continuous Learning: Stay up-to-date with the latest research and developments in machine learning by engaging in brainstorming sessions and deep technical discussions with other experts in the field.
• Flexibility: With a voluntary role, you can contribute as much or as little as your schedule allows, making this position perfect for professionals looking to give back, stay engaged, and expand their skills without the commitment of a full-time role.

Responsibilities:

• Provide strategic advice and high-level guidance on the development of machine learning models, particularly in image analysis and computer vision for vehicle security applications.
• Offer technical mentorship to junior team members and student interns, helping them grow their knowledge and problem-solving skills.
• Participate in brainstorming sessions, providing input on new approaches and innovative ideas to improve model performance and application in security.
• Share best practices, industry insights, and recommendations based on your experience, while also exploring new methodologies and advancements in the field.
• Act as a thought leader, helping guide the direction of ongoing and future projects while contributing your expertise to real-world challenges.

Qualifications:

• Proven experience in machine learning and deep learning, with a focus on computer vision and image processing.
• Strong proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch, OpenCV).
• Expertise in designing, training, and optimizing models such as Convolutional Neural Networks (CNNs).
• Strong communication and leadership skills, with an interest in mentoring and sharing knowledge with a talented team.
• Passion for innovation and a genuine interest in staying updated with advancements in machine learning and security technologies.
• Previous experience in security-related machine learning applications is a plus, but not required.

Commitment & Compensation:
This is a voluntary, unpaid role designed to be flexible and adaptable to your schedule. While no financial compensation is provided, the professional development, networking opportunities, and the chance to influence cutting-edge technology will be immensely beneficial to those seeking leadership and advisory experience in the field of machine learning.