Position: Senior AI Developer (LLM/VLM/Agent Applications)
Senior AI Developer (LLM/VLM/Agent Applications)
Join to apply for the Senior AI Developer role at Autodesk.
The Fusion Machine Learning team is a multi‑disciplinary group of engineers and researchers developing AI/ML solutions to some of the biggest challenges in 3‑D design, manufacturing and mechanical engineering. We are seeking an experienced and passionate Senior AI Developer who leverages LLMOps and Agent Ops practices to build and scale AI applications integrating LLMs, VLMs and agent‑based architectures.
You will collaborate with researchers and engineers to continuously improve data, training and release pipelines by automating repositories to ensure quality and interoperability with deployment systems, and upgrade prototype code to run on a large cloud‑based ML training infrastructure.
You will report to the Fusion Platform ML manager and play a critical role in the Autodesk AI strategy.
The team is hybrid‑remote, located across Canada and the US.
Responsibilities
• AI Application Development:
Develop and enhance AI applications using pre‑trained or existing models (LLMs, VLMs, 3D CAD models) and ensure 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 Agent Ops:
Implement and optimize LLMOps and Agent Ops 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 while collaborating with cross‑functional teams including product managers and UX designers.
Minimum Qualifications
• 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 / Dev Ops in a production environment.
• Experience with industry best practices for developing and maintaining complex codebases.
• Self‑starter with 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.
Preferred Qualifications
• 8+ years of experience in software development.
• Familiarity with agent‑based frameworks such as Lang Flow, Llama Index, Lang Graph and evaluation of agent/LLM/multi‑component pipelines.
• Experience with observability frameworks (Arize, Comet, Phoenix, Langfuse, MLflow, RAGAS, Dynatrace etc.).
• Experience leveraging retrieval‑augmented generation (RAG) techniques.
• 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 (Docker, Kubernetes) for orchestrating and scaling ML applications.
• Experience with AI platforms such as Databricks, Sage Maker, Vertex AI etc.
• Experience with cloud data processing, training, deployment or operations (AWS, GCP).
• Experience developing web applications and APIs.
• Experience 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 inference accelerator tools (ONNX, Tensor
RT, Triton) for real‑time and high‑throughput inference runtimes.
• Experience with CAD software or in design and manufacturing industries.
• Familiarity with machine‑learning, deep‑learning, and statistical modeling tools (PyTorch, Tensor Flow, Pandas, Sci Kit Learn , PySpark).
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