AI/ML Engineer
Role details
Job location
Tech stack
Job description
AI/ML Engineers at our client play a pivotal role in the union of data, systems, and computer sciences. They work closely with a multidisciplinary team, including clinicians, user experience designers, product managers, and IT professionals, to develop and deploy effective, efficient, and ethical AI/ML solutions into clinical practice to enhance patient care and operational efficiency. As an AI/ML Engineer, you will work on the full spectrum of the AI life cycle from ideation to production, leveraging advanced techniques to analyze vast amounts of healthcare data, including patient records, medical imaging, and genomic information., * Work on component design, development, integration, and standardization to create AI-driven solutions that seamlessly integrate into clinical practice
- Collaborate with a multidisciplinary team to understand user needs, workflows, and clinical requirements and assess feasibility
- Interpret and analyze data to inform strategic decisions and communicate complex findings in easily understandable terms
- Leverage machine learning techniques such as deep learning, natural language processing, computer vision, and large language models to design, develop and deploy end-to-end AI solutions
- Participate in the engineering of systems crucial for developing and deploying AI solutions
- Facilitate consistent and automated AI software solution development and releases through the design, testing, and maintenance of tools and associated CI/CD pipelines
- Contribute to implementing best practices and standards for AI development and deployment
- Provide training and education to healthcare staff on the use of AI tools and technologies
Requirements
- Master's degree in Engineering, Computer Science, mathematics, health science, or a related field AND one (1) year of experience; OR Bachelor's degree with three (3) years of experience; OR HS Diploma/GED with seven (7) years of experience
- Experience applying AI and machine learning in production environments, showcasing an understanding of healthcare technology
- Skill in cloud infrastructure environment and software development tools
- Experience working with large, complex, and heterogeneous data sets, preferably in healthcare
- Skill in AI/ML techniques and frameworks
- History of collaborating across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders
- Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities
- Strong interpersonal, communication, and time management skills
Desired skills:
- A Ph.D. in engineering, computer science, health science, or a related analytical/quantitative field
- Expertise in AI/ML techniques and frameworks, such as deep learning, natural language processing, and Generative AI, with proficiency in tools like Python, TensorFlow, PyTorch, sci-kit-learn, Keras, etc
- Knowledge of the healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards
- Familiarity with systems or quality engineering best practices, regulatory standards, and compliance frameworks
- Expertise in user-centered design, human factors engineering, and usability testing methodologies
- Ability to articulate complex technical concepts to diverse audiences
- Experience with healthcare industry informatics standards, best practices, and common data models