AI Developer

You will report to the Fusion Platform ML manager and play a critical role in the Autodesk AI strategy., * AI Application Development: Develop and enhance AI applications using pre-trained or existing models (LLMs, VLMs, 3D CAD models) and ensure the seamless integration of AI components into larger software systems

• End-to-End System Integration: Build and integrate end-to-end systems and applications, focusing on system design, user experience, and application logic
• LLMOps and AgentOps: Implement and optimize LLMOps and AgentOps practices
• Automation and Operational Efficiency: Identify opportunities to streamline processes, automate workflows, and improve research and development velocity
• Best Practices and Governance: Advocate for and establish best practices in code quality, infrastructure maintenance, model governance, security, and compliance
• Design and Collaboration: Participate in design discussions with software architects and researchers, ensuring smooth transitions from research to production. Collaborate with diverse cross-functional teams including product managers and UX designers

• Degree in Data Science, Computer Science, Statistics, or a related field, or equivalent professional experience
• Proficient in Python and at least one other widely used programming language (e.g., C++, Java, JavaScript, etc.)
• 3-5 years of experience in MLOps / DevOps in a production environment
• Experience with industry best practices for developing and maintaining complex codebases
• Self-starter with the initiative to find solutions and solve problems independently
• Comfortable adapting to changing requirements and working in ambiguous areas
• Ability to break down large problems into smaller components and provide clear solutions, * 8+ years of experience in software development
• Agent-Based Frameworks and Tools: Familiarity with advanced frameworks such as LangFlow, LlamaIndex, LangGraph, and agent-based frameworks. Experience with agent/LLM/multi-component pipeline evaluations
• Observability Frameworks: Experience with observability frameworks like Arize, Comet, Phoenix, Langfuse, MLflow, RAGAS, Dynatrace etc.
• Retrieval-Augmented Generation: Experience leveraging retrieval-augmented generation (RAG) techniques
• Context Engineering: Experience with context engineering for enhancing AI model performance
• Experience building reliable and scalable inference APIs (e.g., Flask, FastAPI)
• Proficiency with CI/CD pipelines for machine learning projects
• Expertise in containerization technologies (e.g., Docker, Kubernetes) for orchestrating and scaling machine learning applications
• Experience with AI platforms like Databricks, SageMaker, Vertex AI, etc.
• Experience with cloud data processing, training, deployment, or operations (e.g., AWS, GCP)
• Experience developing web applications and APIs
• Experience in implementing Infrastructure as Code (IaC) using tools like Terraform
• Understanding of security best practices in MLOps, including data encryption, access controls, and compliance standards
• Familiarity with leveraging inference accelerator tools (ONNX, TensorRT, Triton) for real-time and high throughput inference runtimes is a plus
• Experience with CAD software or in the design and manufacturing industries is a plus
• Familiarity with machine learning, deep learning, and statistical modeling tools and libraries (e.g., PyTorch, TensorFlow, Pandas, SciKitLearn, PySpark)

Salary is one part of Autodesk’s competitive compensation package. For Canada-BC based roles, we expect a starting base salary between $123,000 and $180,400. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

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

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