Machine Learning Engineer Resume
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Resume:
- Highly analytical and adaptable professional with advanced knowledge and substantial experience in delivering innovative machine learning solutions that drive business growth and elevate operational efficiency.
- Exceptional ML Engineer; innate ability to design, develop, and implement machine learning models and algorithms that address specific business problems / objectives.
- Quick learner with excellence in software development, machine learning, and data structuring; adept at analyzing large data sets / applying machine learning techniques to model business metrics / generate accurate insights and predictions.
Areas of Expertise
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♦ Machine Learning Model Development ♦ Infrastructure Integration ♦ Technical Leadership |
♦ Model Validation & Deployment ♦ Data Analytics & Structuring ♦ Performance Enhancement |
♦ Process Improvement ♦ Innovative ML Solutions ♦ Cross-functional Collaboration |
Technical Proficiencies
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Programming | Databases: |
Python, React, Java, R, MSSQL, Graph Databases, FastAPi, PySpark |
|
Frameworks | Cloud: |
Azure, Docker, Kubernetes, MLOPs, DataBricks, Weights & Biases |
|
Machine Learning: |
NLP, Computer Vision, NumPy, XGBoost, Pandas, ScikitLearn, and TensorFlow |
Career Experience
Cymax, Toronto – Present
Machine Learning Engineer
Engage with executive team to foster a deeper understanding of technology's transformative potential within organization. Facilitate productive discussions, brainstorming sessions, and collaborate with key stakeholders to identify and explore various business use cases that could benefit from strategic implementation of Artificial Intelligence (AI). Pioneer foundational processes by creating core libraries for reusable code, implementing code reviews, and refining the Git strategy. Elevate ML model and code quality along with fostering culture of growth and excellence through effective feedback and mentorship.
- Achieved estimated annual profit increase of $k and $M sales boost by integrating MSSQL, React, FastAPI, and Azure Kubernetes into Python ML applications developed with core OOP principles.
- Reduced manual grouping time by hours per week while enhancing accuracy by implementing NLP and computer vision techniques for detailed product attribute representations.
- Spearheaded design of ML systems for robustness and scalability while serving as lead architect for % of projects.
- Introduced ChatGPT via Prompt Engineering for a wide range of company-wide initiatives, amplifying our capabilities and fostering innovative solutions.
OTPP, Toronto
Data Analyst (Investments)
Collaborated with stakeholders to align ML solutions with needs and seamlessly integrate into existing infrastructure while ensuring optimal performance. Supported investment decision-making processes by collecting, analyzing, and interpreting financial and investment data. Performed quantitative analysis and modeling to assess investment risks and opportunities. Developed and maintained financial models to evaluate investment scenarios and outcomes.
- Ensured data accuracy and consistency in Oracle database by utilizing SQL to maintain financial time-series data.
- Identified opportunities for automation using ML models / contributed suggestions to enhance operational efficiency.
Wirecard, Toronto –
Developer
Designed and maintained software applications and systems for payment processing and financial services. Developed and maintained databases, ensuring data integrity and security. Integrated with various payment gateways, financial institutions, and third-party APIs to facilitate seamless transactions.
- Improved product quality and performance while contributing to API development using Java and Node.js.
- Increased bug detection and ensured production deployment through engineering of Selenium and Groovy scripts.
Education
Bachelor of Science in Computer Science with Honors | York University, Dean’s List
Diploma in Software Engineering | Centennial College
Licenses & Certifications
Azure AI Engineer, Deep learning Specialization
