Principal Machine Learning Developer (AI/ML Platform)
Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Oct 2, 2026. Autodesk scores B on the Alion truth index.
Join Autodesk as a Principal Machine Learning Developer, where you will drive the operational excellence and technical direction of our AI/ML Platform. You will lead the design and engineering of software systems and platform services, implement automated deployment pipelines, and collaborate with cross-functional teams to maintain scalable infrastructure. You will also develop tools for building, deploying, and operating ML artifacts, automate data transformation tasks, and design low-latency prediction services. Additionally, you will enforce security best practices, identify opportunities for process optimization, and take ownership of critical platform components.
Missions
- Drive the operational excellence and technical direction of the AI/ML Platform by implementing and optimizing MLOps practices across the full machine learning development lifecycle.
- Lead the design and engineering of software systems and platform services for the AI/ML Platform, contributing to scalable, secure, and reliable ML development and operations.
- Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, data processing, and ML artifact management.
Profil recherché
- Strong background in AI/ML with experience in deep learning, statistical modeling, and neural networks- Ability to tackle complex technical challenges, analyze potential solutions, and implement the most effective ones
- Strong communication skills to effectively collaborate with cross-functional teams, along with the ability to work independently
- 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
- BS or MS in Computer Science, or equivalent practical experience
- Deep understanding of performance metrics and latency optimization techniques, with the ability to diagnose, tune, and enhance the efficiency of serving systems
- Experience: 8+ years of experience in software development and engineering, with a solid record of delivering production systems and services
- A continuous learning mindset to stay updated with the latest trends and technologies in AI/ML, cloud computing, and software engineering
- Strong coding skills in languages commonly used in AI/ML and system development, such as Python, Java, or Go
- Experience with big data technologies and ecosystems (Hadoop, Spark, Kafka) for processing and analyzing large datasets in a distributed computing environment
- 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
- Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard)
- Experience with HPC techniques and technologies for optimizing computational workloads, particularly in the context of AI/ML model training and inference