Senior Principal Machine Learning Engineer
Autodesk, Richmond, VA, United States
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
Are you an existing contractor or consultant with Autodesk?
Please search for open jobs and apply internally (not on this external site).
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
Are you an existing contractor or consultant with Autodesk?
Please search for open jobs and apply internally (not on this external site).