US-MN-Maple Grove
About the role:
In this newly created role, you will be at the forefront of innovation, designing and developing Artificial Intelligence (AI) models that produce high-quality, creative outputs. Collaborating closely with a team of automation specialists and product managers, you will develop AI-driven solutions that meet business objectives and elevates user experiences.
Your responsibilities will include:
- Design, implement, and optimize generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based architectures for various applications, including text, image, and audio generation.
- Work with large datasets, perform data preprocessing and augmentation, and ensure the quality and integrity of training data.
- Stay up-to-date with the latest research in generative Artificial Intelligence (AI) and Machine Learning (ML), and apply new techniques to enhance model performance and capabilities.
- Collaborate with cross-functional teams to understand project requirements, define AI solutions, and integrate models into production systems.
- Monitor and optimize the performance of generative models, including tuning hyperparameters, reducing latency, and improving the scalability of AI systems.
- Maintain comprehensive documentation of model architectures, training processes, and performance metrics.
- Develop and implement rigorous testing and validation protocols to ensure the robustness and reliability of AI models.
- Provide guidance and mentorship to junior developers and interns, fostering a collaborative and growth-oriented work environment.
Required Qualifications:
- Bachelor's degree in computer science, engineering, or a related field.
- 3+ years of experience in the Artificial Intelligence (AI) and Machine Learning (ML) development lifecycle, with a focus on generative models.
- Proficiency in Python and relevant machine learning (ML) libraries/frameworks such as Streamlit, TensorFlow, PyTorch, and Scikit-Learn.
- Experience with generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based architectures.
- Strong understanding of deep learning techniques, neural network architectures, and software engineering principles.
- Familiarity with cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, as well as containerization technologies like Docker and Kubernetes.
- Experience with data preprocessing, augmentation, and working with large-scale datasets.
- Demonstrated strong communication skills and ability to work effectively in a team environment.
- Proven ability to manage multiple projects and meet deadlines.
Preferred Qualifications:
- Advanced degree in computer science, engineering, or a related field.
- Experience with natural language processing (NLP), computer vision, or audio processing.
- Knowledge of reinforcement learning or unsupervised learning techniques.
- Contributions to open-source projects in the Artificial Intelligence (AI) and Machine Learning (ML) domain.
Please be advised that certain US based positions, including without limitation field sales and service positions that call on hospitals and/or health care centers, require acceptable proof of COVID-19 vaccination status. Candidates will be notified during the interview and selection process if the role(s) for which they have applied require proof of vaccination as a condition of employment. Boston Scientific continues to evaluate its policies and protocols regarding the COVID-19 vaccine and will comply with all applicable state and federal law and healthcare credentialing requirements. As employees of the Company, you will be expected to meet the ongoing requirements for your roles, including any new requirements, should the Company’s policies or protocols change with regard to COVID-19 vaccination.