Software Engineer(AI/ML Platform)

Autodesk; Pune District; Hybrid; INR 1,400,000 - 2,100,000; Full time

Job summary

Autodesk in Pune is seeking a Senior Software Engineer to design and implement scalable AI/ML serving systems within a hybrid cloud architecture. You will drive deployment, monitoring, and optimization while collaborating with researchers and data engineers to translate models into production-ready solutions.

The role requires 2–5 years of software development experience, proficiency in Python, TensorFlow/PyTorch, and hands-on cloud experience (AWS/Azure/GCP) with Docker/Kubernetes.

Qualifications

• BS or MS in Computer Science or equivalent practical experience.
• 2–5 years of software development and engineering delivering production systems.
• Hands-on experience with AI/ML frameworks and model deployment lifecycle.

Responsibilities

• Design scalable AI/ML serving systems for varying loads and low latency.
• Manage hybrid cloud architecture across on‑premises and cloud platforms (AWS/Azure/GCP).
• Oversee deployment of AI/ML models with CI/CD pipelines and versioning.
• Implement monitoring and optimization to reduce costs and improve performance.
• Ensure data security and regulatory compliance in serving platforms.
• Collaborate with researchers and engineers to translate models into production systems.
• Stay updated on AI/ML, cloud, and software engineering practices.

Skills

Python

TensorFlow

PyTorch

CI/CD

Cloud architectures

Linux

Model serving

Education

BS or MS in Computer Science

Tools

Docker

Kubernetes

AWS

Azure

GCP

Terraform

Job description

Job Requisition ID #

26WD96776

Position Overview

We are looking for an experienced Senior Software Engineer to join the AMP team, focusing on the design of our AI/ML serving platform within a hybrid cloud architecture. This important role involves architecting scalable, efficient systems for model serving and inference, ensuring seamless deployment and management across diverse environments. You will have a background in software engineering, with an understanding of AI/ML technologies, and experience managing hybrid cloud infrastructures. As an important contributor to our engineering team, you will help shape the future of our AI/ML capabilities, delivering solutions that inspire value for our organization. You will report to Manager. You will work from Pune location, and your jobs workplace type will be hybrid.

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 optimise 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

Minimum Qualifications

• Educational Background: BS or MS in Computer Science, or equivalent practical experience
• Experience: 2 to 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

• 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 / À propos d’Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. 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 – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Bienvenue chez Autodesk! Nos logiciels créent chaque jour des choses extraordinaires: des bâtiments les plus écologiques aux voitures les plus propres, en passant par les usines les plus intelligentes et les films à succès.

Nous sommes très fiers de notre culture chez Autodesk; elle est au cœur de tout ce que nous faisons. Notre culture guide notre façon de travailler et de nous comporter les uns envers les autres, influence nos interactions avec nos clients et nos partenaires, et définit notre image au monde.

En tant qu’Autodeskien, vous pouvez accomplir un travail significatif qui contribue à bâtir un monde meilleur, conçu et réalisé pour tous. Prêt à façonner le monde et votre avenir? Rejoignez-nous!

Salary transparency / Transparence Salariale

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, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.