Senior Principal Machine Learning Engineer

Job Requisition ID #

26WD94803

Senior / Principal Research Engineer, Foundation Model Systems

Position Overview

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter. Autodesk is seeking a Senior / Principal Research Engineer, Foundation Model Systems to help scale the next generation of foundation models trained on Autodesk-native design and make data. In this role, you will work at the intersection of research and engineering to build, optimize, and evolve the systems that power large-scale training, post-training, evaluation, deployment, and inference for foundation models. This is a deeply technical role for an engineer who understands how model capability, system design, and infrastructure efficiency interact. You will help researchers train and iterate faster, improve utilization of compute resources, scale distributed training pipelines, and optimize inference systems for latency, throughput, reliability, and cost. You will also help strengthen the surrounding ML platform capabilities required for reproducibility, observability, lineage, governance, and production readiness. This role is central to Autodesk’s broader foundation model strategy, which depends on scaling shared models trained on structured Design and Make data and turning them into reusable capabilities across products and workflows.

Location: US or Canada Remote

Responsibilities

• Architect, build, and optimize large-scale training systems for foundation models, including pre-training, fine-tuning, and post-training workflows
• Improve distributed training performance across data, tensor, model, and pipeline parallelism strategies
• Scale and optimize training pipelines for throughput, stability, memory efficiency, checkpointing, and experiment velocity
• Design and improve inference systems for low latency, high throughput, high reliability, and cost-efficient serving
• Develop and operationalize techniques such as batching, scheduling, KV cache optimization, quantization, speculative decoding, Flash Attention, and memory-efficient serving
• Partner closely with researchers to turn promising modeling work into scalable, repeatable engineering systems
• Evaluate and adopt the right optimization and scaling frameworks for different model sizes and workloads
• Build robust evaluation, profiling, and benchmarking workflows to guide decisions around scaling, architecture, and ROI
• Improve observability, model performance monitoring, prediction logging, lineage, and debugging across training and inference systems
• Contribute to deployment workflows, model lifecycle tooling, and production ML infrastructure
• Strengthen engineering practices across testing, CI/CD, reliability, release readiness, and incident response for ML systems
• Collaborate across research, platform, product, and infrastructure teams to align technical investments with product and business goals

Minimum Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related field, or equivalent
• Industry Experience
• Strong experience building and operating large-scale machine learning systems in production or research-to-production environments
• Deep experience with distributed systems and distributed training for deep learning workloads
• Strong proficiency in Python and strong software engineering fundamentals
• Experience with PyTorch and modern large-model training stacks
• Experience with at least some of the following: FSDP, DeepSpeed, Megatron-LM, DDP, tensor parallelism, pipeline parallelism, or equivalent approaches
• Experience optimizing training performance, GPU utilization, memory footprint, and iteration speed
• Experience designing or operating inference systems for production ML workloads
• Experience with cloud and cluster environments, containers, CI/CD, and modern infrastructure practices
• Experience with monitoring, profiling, logging, and observability for ML systems
• Strong communication skills and the ability to work effectively across research and engineering teams

Preferred Qualifications

• Experience scaling foundation model or large-model training pipelines
• Experience with RLHF, RL-based post-training, preference optimization, or other alignment / post-training workflows
• Experience with inference frameworks and runtimes such as vLLM, TensorRT-LLM, TGI, Ray Serve, or equivalent systems
• Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
• Experience with model deployment, inference services, monitoring, and observability for production ML systems
• Experience with data lineage, provenance, governance, and responsible data usage in ML systems
• Experience building data pipelines for large-scale structured and semi-structured technical datasets
• Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data
• Experience profiling and optimizing long-context or memory-intensive transformer workloads
• Experience with Kubernetes, Docker, experiment tracking systems, model registries, and reproducible ML workflows
• Familiarity with CAD, BIM, AEC, manufacturing, simulation, or other complex technical design domains is a plus

The Ideal Candidate

• Is equally comfortable talking to research scientists and platform engineers
• Thinks in systems, not just models
• Understands that scaling is a multi-dimensional problem involving compute, performance, latency, throughput, cost, and operational complexity
• Can move fluidly between hands-on debugging, architectural design, and longer-term platform thinking
• Brings strong judgment on when to optimize the current stack and when to evolve the stack
• Cares deeply about turning research capabilities into durable, reusable engineering systems

Learn More

About 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!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $165,000 and $296,450. 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.

Equal Employment Opportunity

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

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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