Keras Developer

Vintti is a staffing agency that leverages the geographical advantage of Latin America to benefit US businesses. We connect companies with professionals who work in time zones closely aligned with or identical to US hours, ensuring seamless communication and collaboration. This synchronicity allows for real-time interaction, enhancing productivity and eliminating the delays often associated with offshore staffing.

A Keras Developer is a specialized professional who leverages the Keras deep learning framework to build, train, and optimize neural network models. They work extensively with Python and integrate Keras with other libraries like TensorFlow to craft robust machine learning solutions. Their expertise includes designing both simple and complex architectures, such as CNNs and RNNs, to address various AI challenges. Keras Developers also focus on data preprocessing, model evaluation, and fine-tuning hyperparameters to improve model performance, making significant contributions to advancing AI capabilities within diverse applications.

- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field
- Proven experience in developing and training deep learning models using the Keras framework
- Strong proficiency in Python programming language
- Solid understanding of machine learning and deep learning concepts and algorithms
- Experience with data preprocessing techniques such as cleaning, augmentation, and normalization
- Familiarity with other deep learning frameworks such as TensorFlow or PyTorch
- Experience with model evaluation, validation, and testing methodologies
- Knowledge of techniques for optimizing and fine-tuning models for performance and scalability
- Ability to develop custom layers and functions for specialized deep learning tasks
- Experience integrating deep learning models into production systems and applications
- Strong problem-solving skills and ability to debug and troubleshoot issues related to model training and deployment
- Proficiency with version control systems such as Git
- Ability to stay updated with the latest research and advancements in deep learning and the Keras framework
- Excellent written and verbal communication skills, including the ability to write thorough documentation
- Experience providing technical support and mentorship to junior developers and team members
- Strong collaboration skills and ability to work effectively in a team environment
- Experience in conducting model experimentation and hyperparameter tuning
- Strong analytical and critical thinking skills

- Design and develop deep learning models using the Keras framework
- Train deep learning models to meet specific project goals
- Preprocess and prepare data for model training, including cleaning, augmentation, and normalization
- Collaborate with data scientists and machine learning engineers to understand and implement project requirements
- Select appropriate layers, activations, and optimizers for model architecture
- Conduct thorough evaluation, validation, and testing of models
- Optimize and fine-tune models for performance and scalability
- Develop custom layers and functions as needed for specific projects
- Integrate deep learning models with existing systems and applications
- Experiment with model architectures and hyperparameters to achieve optimal performance
- Troubleshoot and debug issues related to model training and deployment
- Use version control systems to manage and document code changes
- Stay informed about the latest advancements in deep learning and the Keras framework
- Write and maintain comprehensive documentation for model development and implementation processes
- Provide technical support and mentorship to junior developers and team members
- Actively participate in team meetings and contribute to project planning and strategy sessions

The ideal candidate for the Keras Developer role is a highly skilled professional with a strong background in computer science, electrical engineering, data science, or a related field, holding at least a Bachelor’s or Master’s degree. They possess proven experience in designing, developing, and training deep learning models using the Keras framework, along with a solid proficiency in Python. With a deep understanding of machine learning and deep learning concepts and algorithms, they are adept at data preprocessing, including cleaning, augmentation, and normalization techniques. They are familiar with other deep learning frameworks like TensorFlow or PyTorch and have a keen ability to evaluate, validate, and test models, ensuring performance and scalability. Their expertise includes developing custom layers and functions tailored to specific project requirements and integrating these models into production systems seamlessly. The ideal candidate is a strong problem-solver, capable of debugging and troubleshooting complex issues, and proficient in using version control systems such as Git. They keep abreast of the latest advancements in deep learning and the Keras framework, and excel at communicating complex technical concepts through clear documentation and effective verbal communication. A natural mentor, they provide technical support and guidance to junior developers, exhibiting excellent collaboration skills to work harmoniously within a team. Their analytical and critical thinking abilities are complemented by creativity in designing innovative solutions. They maintain a high level of attention to detail and precision, demonstrating resilience and persistence in facing challenges. Organized and proactive, the ideal candidate is committed to delivering high-quality work on time, continuously seeking improvement and innovation. They are versatile, adaptable to different projects and application domains, and driven by a passion for staying updated in a rapidly evolving field.

- Design, develop, and train deep learning models using the Keras framework
- Collaborate with data scientists and machine learning engineers to understand project requirements and objectives
- Preprocess and prepare data, including data cleaning, augmentation, and normalization
- Implement model architecture, including selecting appropriate layers, activations, and optimizers
- Conduct model evaluation, validation, and testing to ensure performance metrics meet project standards
- Fine-tune and optimize models for efficiency and scalability
- Develop custom layers and functions for specific project needs
- Integrate deep learning models with existing systems and applications
- Perform model experimentation and hyperparameter tuning to achieve optimal results
- Debug and troubleshoot issues related to model training and deployment
- Utilize version control systems to manage and document code changes
- Stay updated with the latest research and advancements in deep learning and the Keras framework
- Write and maintain clear, detailed documentation for all aspects of model development and implementation
- Provide technical support and mentorship to junior developers and team members
- Participate in team meetings and contribute to project planning and strategy discussions

- Strong analytical and critical thinking abilities
- Excellent problem-solving skills
- High level of attention to detail and precision
- Effective communication and collaboration skills
- Ability to work independently and as part of a team
- Eagerness to learn and stay updated with advancements in deep learning
- Creativity in designing and optimizing model architectures
- Resilience and persistence in troubleshooting and debugging
- Ability to translate complex concepts into clear and comprehensive documentation
- Technical mentorship skills to support junior developers
- Strong organizational and project management skills
- Proactive attitude towards continuous improvement and innovation
- Commitment to delivering high-quality work within deadlines
- Versatility in adapting to different projects and application domains

- Competitive salary ranging from $90,000 to $130,000 per year, depending on experience and qualifications
- Comprehensive health, dental, and vision insurance plans
- Flexible working hours to support work-life balance
- Opportunity for remote work or hybrid remote/on-site work arrangements
- Generous paid time off, including vacation days, sick leave, and holidays
- Professional development opportunities, including training programs, workshops, and conferences
- Access to cutting-edge technology and tools for model development and experimentation
- Mentorship programs and opportunities for career growth within the company
- Collaborative and inclusive work environment
- Employee assistance programs for mental health and well-being
- Retirement savings plan with company matching contributions
- Stock options or performance-based bonuses
- Casual dress code and comfortable office environment
- Subsidized on-site gym membership or wellness programs
- Regular team-building activities and social events
- Free snacks and beverages in the office
- Transportation or commuting subsidies