Senior AI/ML Engineer
4 weeks ago
Position Overview
We are seeking an experienced Senior Software Engineer to join our AI/ML team, focusing on the design of our AI/ML serving platform within a hybrid cloud architecture. This critical role involves architecting scalable, efficient systems for model serving and inference, ensuring seamless deployment and management across diverse environments.
Key Responsibilities
- Design and Implement Scalable AI/ML Serving Systems: Develop scalable and efficient systems for serving AI/ML models, ensuring that these systems can handle varying loads and perform with low latency across diverse environments.
- Hybrid Cloud Architecture Management: Architect and manage a hybrid cloud environment that uses both on-premises resources and multiple cloud platforms (e.g., AWS, Azure, GCP) to optimize performance, cost, and scalability.
- Model Deployment and Versioning: Oversee the deployment of AI/ML models into production, including the setup of CI/CD pipelines for model deployment and versioning, ensuring smooth and reliable model updates and rollbacks.
- Performance Monitoring and Optimization: Implement monitoring tools and practices to track the performance of AI/ML models in production, identifying bottlenecks and optimizing system and model performance for better efficiency and reduced costs.
- Security and Compliance: Ensure that the AI/ML serving systems follow industry standards and regulatory requirements for data security and privacy, including the management of data encryption, access controls, and audit trails.
- Collaboration and Leadership: Work closely with AI/ML researchers, data engineers, and other partners to translate complex AI/ML models into production-ready systems, providing technical guidance throughout the project lifecycle.
- Research and Innovation: Stay informed about the latest developments in AI/ML technologies, cloud computing, and software engineering practices, exploring and integrating solutions that can enhance the capabilities and efficiency of the AI/ML serving platform.
Requirements
- Education: BS or MS in Computer Science, or equivalent practical experience.
- Experience: 5+ years of experience in software development and engineering, with a solid record of delivering production systems and services.
- Expertise in AI/ML Technologies: Hands-on experience with AI/ML frameworks (such as TensorFlow, PyTorch) and familiarity with the lifecycle of AI/ML model development, from training to deployment.
- Proficiency in Programming Languages: Strong coding skills in languages commonly used in AI/ML and system development, such as Python.
- Experience with Cloud Technologies: Experience with designing and managing systems on hybrid cloud architectures, including working knowledge of cloud service providers like Azure.
- Knowledge of Containerization and Orchestration Tools: Familiarity with containerization technologies (e.g., Docker) and orchestration systems (e.g., Kubernetes), crucial for deploying and scaling applications in a cloud environment.
- Understanding of DevOps Practices: Knowledge of CI/CD pipelines, infrastructure as code, and other DevOps practices to ensure smooth deployment and operation of AI/ML systems.
- System Performance Optimization: Deep understanding of performance metrics and latency optimization techniques, with the ability to diagnose, tune, and enhance the efficiency of serving systems.
Preferred Qualifications
- GPU Computing: Exposure to leveraging GPU computing for AI/ML workloads, including experience with CUDA, OpenCL, or other GPU programming tools, to significantly enhance model training and inference performance.
- Cloud Certifications: Certifications in cloud technologies from major providers (AWS Certified Solutions Architect, Google Cloud Professional Cloud Architect, Microsoft Certified: Azure Solutions Architect Expert), indicating a high level of expertise in cloud services and architecture.
- Experience with Big Data Technologies: Experience with big data technologies and ecosystems (Hadoop, Spark, Kafka) for processing and analyzing large datasets in a distributed computing environment.
- AI/ML Model Monitoring Tools: Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard).
About Autodesk
Welcome to Autodesk. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers.
When you're an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us
Salary transparency
Salary is one part of Autodesk's competitive compensation package. Offers are based on the candidate's experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package.
Diversity & Belonging
We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here:
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