AI Engineer supporting a leading healthcare client with GenAI and ML solutions. Position focuses on building and deploying scalable AI applications in GCP environments.
About the role
- Senior Software Development Manager leading enterprise-scale AI/ML platform development at Autodesk. Guiding a team of software and ML engineers in building innovative solutions.
Responsibilities
- Lead and mentor a team of engineers in the development and deployment of AI/ML solutions
- Collaborate with cross-functional teams including product management, data science, data, and cloud infrastructure to define and execute the AI/ML platform roadmap
- Provide guidance to the design and architecture of scalable, reliable, and efficient AI/ML systems and drive critical technology decisions
- Driving the execution of the platform strategy following principles of agile methodology and best practices in software development, code quality, and security standards
- Create and manage plans, track, and ensure tactical execution and adherence to budgets, schedules, plans, and performance
- Actively participate in coding review processes, and problem-solving alongside your team
- Build and foster a high-performance culture, mentor team members and provide your team with the tools and motivation to make things happen
- Actively participate in the hiring process to attract and onboard top-tier development talent, ensuring the team possesses the necessary skills and expertise to execute on the AI/ML platform vision
Requirements
- BS/MS in Computer Science, Engineering, or a related field
- 12+ years of experience of software development with 3+ years of experience as a manager
- Proven experience leading and mentoring software and ML development teams
- Experience with design, build and running scalable, high-performance systems production applications on cloud platforms such as AWS, Azure, or Google Cloud Platform and containerization technologies (Docker, Kubernetes)
- Experience building and deploying AI models, for rapid AI application development, using AWS SageMaker, Bedrock or Azure Machine Learning
- Experience working with complex agentic AI architectures, API ecosystems, guardrails, context management and other best of breed AI/ML offerings
- Understanding of MLOps principles and practices for effectively managing and automating machine learning workflows, including model versioning, monitoring, and deployment
- Expertise in CI/CD, automation tools, and practices for machine learning lifecycle management
- Strong background in AI/ML with experience in deep learning, statistical modeling, and neural networks
- Experience with Scrum and agile development processes and methodologies.
Benefits
- Annual cash bonuses
- Stock grants
- Comprehensive benefits package
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