Boston Scientific AI/IA Software Developer 

Costa Rica, Alajuela Province, El Amparo 

401945748

Costa Rica-Coyol

Your responsibilities will include:

• Model Development: Design, implement, and optimize generative models (e.g., GANs, VAEs, Transformers) for various applications, including text, image, and audio generation.
• Data Management: Work with large datasets, perform data preprocessing, augmentation, and ensure the quality and integrity of training data.
• Research and Innovation: Stay up to date with the latest research in generative AI and machine learning and apply new techniques to enhance model performance and capabilities.
• Collaboration: Collaborate with cross-functional teams to understand project requirements, define AI solutions, and integrate models into production systems.
• Performance Optimization: Monitor and optimize the performance of generative models, including tuning hyperparameters, reducing latency, and improving the scalability of AI systems.
• Documentation: Maintain comprehensive documentation of model architectures, training processes, and performance metrics.
• Testing and Validation: Develop and implement rigorous testing and validation protocols to ensure the robustness and reliability of AI models.
• Mentorship: Provide guidance and mentorship to junior developers and interns, fostering a collaborative and growth-oriented work environment.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication skills and ability to work effectively in a team environment.
• Ability to manage multiple projects and meet deadlines.

Required qualifications:

• Bachelor's or master’s degree in computer science, Engineering, or a related field.
• 3+ years of experience in AI/ML development life cycle, with a focus on generative models.
• Proficiency in Python and relevant ML libraries/frameworks (e.g., StreamLit, TensorFlow, PyTorch, Scikit-Learn).
• Experience with generative models such as GANs, VAEs, and Transformer-based architectures.
• Strong understanding of deep learning techniques, neural network architectures and software engineering principles.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes).
• Experience with data preprocessing, augmentation, and working with large-scale datasets.

Preferred qualifications:

• Experience with NLP, computer vision, or audio processing.
• Knowledge of reinforcement learning or unsupervised learning techniques.
• Contributions to open-source projects in the AI/ML domain.