About Company
Imagine a place where your groundbreaking ideas in AI are not just heard, but actively integrated into real-world solutions. Career.zycto is that environment, a dynamic tech innovator deeply committed to pushing the boundaries of machine intelligence. We thrive on complex challenges, fostering a culture of curiosity and continuous learning. For a Deep Learning Engineer, this means unparalleled opportunities to develop cutting-edge algorithms, work with rich datasets, and see the tangible impact of your work. Join us and shape the future of intelligent systems, making a significant mark in a collaborative and forward-thinking team.
Job Description
Are you a visionary Deep Learning Engineer passionate about transforming data into intelligent systems? Career.zycto is seeking a talented individual to join our innovative team in St. John’s, Newfoundland and Labrador. This is a unique opportunity to apply your expertise in neural networks, machine learning, and artificial intelligence to solve complex, real-world problems across various domains. As a Deep Learning Engineer, you will be instrumental in designing, developing, and deploying advanced AI models that drive our next generation of products and services. You’ll work alongside a diverse group of engineers, data scientists, and product managers, contributing to the full lifecycle of our AI-powered solutions – from ideation and research to implementation and optimization. We are looking for someone who thrives in a fast-paced environment, embraces continuous learning, and is eager to make a tangible impact on our technological landscape. If you possess a strong analytical mind, exceptional programming skills, and a genuine curiosity for the frontiers of deep learning, we encourage you to apply and help us build the future.
Key Responsibilities
- Design, develop, and implement state-of-the-art deep learning models for various applications including computer vision, natural language processing, and predictive analytics.
- Perform extensive data preprocessing, feature engineering, and data augmentation to prepare datasets for model training.
- Evaluate and optimize deep learning model performance, accuracy, and efficiency using rigorous experimental methodologies.
- Collaborate with data scientists, software engineers, and product managers to integrate deep learning solutions into existing and new products.
- Research and stay up-to-date with the latest advancements in deep learning algorithms, frameworks, and tools.
- Document model architectures, training procedures, and deployment strategies.
- Contribute to the scaling and deployment of deep learning models in production environments.
- Participate in code reviews, foster best practices, and mentor junior team members.
Required Skills
- Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Strong understanding of various neural network architectures (CNNs, RNNs, Transformers, GANs, etc.) and their applications.
- Experience with data manipulation and analysis libraries (e.g., NumPy, Pandas, Scikit-learn).
- Solid foundation in machine learning principles, statistics, and linear algebra.
- Familiarity with cloud platforms (AWS, Azure, GCP) for model training and deployment.
- Excellent problem-solving skills and the ability to work independently and collaboratively.
- Strong communication skills, both written and verbal.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow).
- Knowledge of distributed computing frameworks (e.g., Apache Spark).
- Experience with version control systems (e.g., Git).
- Publications in relevant AI/ML conferences or journals.
- Experience working with large-scale datasets and high-performance computing.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and flexible work arrangements.
- Opportunities for professional development, conferences, and certifications.
- Collaborative and innovative work environment.
- State-of-the-art tools and technologies.
- Access to mentorship and career growth programs.
- Regular team-building activities and social events.
How to Apply
Ready to shape the future of AI? Click on the application link below to submit your resume and cover letter. Please highlight your experience with deep learning projects and any relevant publications or GitHub repositories. We look forward to reviewing your application!
