Cloud Engineer (AI/ML, AWS/Azure)

Autodesk - Sunriver, OR

Full-time - Mid Level

Sunriver, OR

Publishing Industries

About the position

We are looking for an experienced Cloud Software Engineer to join our platform team focusing on AI/ML Platform (AMP). This team is responsible for building and maintaining central components that fast track the development of new ML/AI models, including model development studio, feature store, model serving, and model observability. As a key contributor to our engineering team, you will play a crucial role in shaping the future of our AI/ML capabilities, delivering solutions that provide significant value to our organization. You will collaborate with other senior engineers and report directly to the engineering manager. This position is based in Bangalore and follows a hybrid workplace model. In this role, you will be tasked with designing, implementing, and managing software systems for the AI/ML Platform, orchestrating the full ML development lifecycle for partner teams. You will define components that leverage the strengths of multiple cloud platforms, such as AWS and Azure, to optimize performance, cost, and scalability. Additionally, you will develop comprehensive systems to automate and optimize laborious processes, integrating them seamlessly into our platform to streamline operations. You will also be responsible for building systems for monitoring the performance of AI/ML models, identifying insights on underlying data, and detecting issues such as drift detection, data fairness/bias, and anomalies. Your work will involve developing tools for building and deploying ML artifacts in production environments, ensuring a smooth transition from development to deployment. Furthermore, you will automate and orchestrate tasks related to managing big data transformation and processing, building large-scale data stores for ML artifacts, and designing low-latency, scalable prediction and inference services to support diverse user needs. Collaboration across various teams, including machine learning researchers, developers, product managers, software architects, and operations, will be essential to foster a cohesive work environment.

Responsibilities

• Design, implement and manage software systems for the AI/ML Platform, orchestrating the full ML development lifecycle for partner teams.
• Define components leveraging strengths from multiple cloud platforms (e.g., AWS, Azure) to optimize performance, cost, and scalability.
• Develop comprehensive systems to automate and optimize laborious processes, integrating them seamlessly into our platform.
• Build systems for monitoring performance of AI/ML models and finding insights on underlying data such as drift detection, data fairness/bias, and anomalies.
• Develop tools for building and deploying ML artifacts in production environments, facilitating a smooth transition from development to deployment.
• Automate and orchestrate tasks related to managing big data transformation and processing, building large-scale data stores for ML artifacts.
• Design and implement low-latency, scalable prediction, and inference services to support diverse user needs.
• Collaborate across diverse teams, including machine learning researchers, developers, product managers, software architects, and operations.

Requirements

• Bachelor's degree in Computer Science or equivalent practical experience.
• 2+ years of experience in software development and engineering, delivering production systems and services.
• Prior experience working on MLOps or data engineering projects.
• Ability to fluently translate design into functional code in programming languages such as Python, Golang, or Java.
• Prior experience of end-to-end ownership at the product feature level, including requirements gathering, planning/estimations, implementation, verification, rollout, and troubleshooting.
• Prior experience of building REST APIs, integrations with cloud technologies, databases, and observability tools.
• Exposure to DevOps practices, containerization, and orchestration tools such as CI/CD, Terraform, Docker, and Kubernetes.
• Demonstrated creative problem-solving skills with the ability to break down problems into manageable sub-problems.
• Experience on Amazon AWS or Azure cloud (beyond Virtual machines, blob storage).

Nice-to-haves

• Prior collaborations with Data science teams to understand ML terminologies and their pain-points.
• Prior experience of on-call rotation for tier-1 services with 24x7 support mechanism.

Benefits

• Competitive salary package with discretionary annual cash bonuses and commissions for sales roles.
• Stock or long-term incentive cash grants.
• Comprehensive benefits package.