Position Title: Machine Learning Expert

Employment Type: Contractor (Paid)

Location: Toronto, ON, Canada

Duration: 4 months

Compensation: $40-50/hr

About Us: Avolta Inc. is a leading innovator in automotive security, committed to leveraging advanced technologies to solve complex problems and drive progress. Our team is comprised of experts in various domains, dedicated to excellence and continuous improvement. We are currently seeking a seasoned Machine Learning Expert to join our dynamic team on a contract basis.

Position Overview: The Machine Learning Expert will be responsible for developing, implementing, and optimizing machine learning models to address critical business challenges. This role requires a deep understanding of machine learning algorithms, data analysis, and model deployment. The ideal candidate will have extensive experience in applying machine learning techniques to real-world problems and a strong ability to communicate complex technical concepts to non-technical stakeholders.

Key Responsibilities:

• Model Development: Design, develop, and implement machine learning models to solve specific business problems.
• Data Analysis: Perform exploratory data analysis and preprocessing to ensure high-quality data inputs for modeling.
• Algorithm Selection: Identify and apply appropriate machine learning algorithms based on project requirements.
• Model Training and Evaluation: Train, validate, and fine-tune models to achieve optimal performance metrics.
• Deployment and Integration: Deploy models into production environments and ensure seamless integration with existing systems.
• Performance Monitoring: Continuously monitor model performance and make necessary adjustments to maintain accuracy and efficiency.
• Documentation: Maintain comprehensive documentation of models, methodologies, and processes.
• Collaboration: Work closely with cross-functional teams, including data engineers, software developers, and business analysts, to ensure successful project delivery.
• Innovation: Stay updated with the latest advancements in machine learning and proactively propose innovative solutions to enhance our capabilities.

Required Qualifications:

• Education: Completed Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field.
• Experience: Minimum of 3 years of professional experience in machine learning, with a proven track record of successful projects.
• Technical Skills:
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of statistical methods and data preprocessing techniques.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) for model deployment.
• Analytical Skills: Ability to analyze complex datasets and derive actionable insights.
• Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex concepts to non-technical audiences.
• Problem-Solving Skills: Strong analytical and problem-solving abilities, with a proactive approach to identifying and resolving issues.

Preferred Qualifications:

• Experience working with Machine Learning Models written in Python.
• Knowledge of big data technologies (e.g., Hadoop, Spark).
• Familiarity with DevOps practices for machine learning (e.g., MLOps).

How to Apply: Interested candidates are invited to submit their resume, a cover letter detailing their relevant experience, and examples of past machine learning projects to [email protected].

Application Deadline: June 01, 2024

Equal Opportunity Employer: Avolta Inc. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Join Us: If you are a passionate machine learning professional looking for an exciting opportunity to make a significant impact, we encourage you to apply. Join Avolta Inc. and be a part of our journey to drive innovation and excellence.

For any queries, please contact [email protected].