Interested in this AI/ML Engineer role at Autodesk?
Apply Now →Skills & Technologies
About This Role
Job Requisition ID \#
26WD100467*L'affichage de poste en français suivra / The French job posting follows.*26WD100467, AI Builder, Principal Experience Designer
Position Overview
This is a role for an experience design leader who wants to fundamentally change how the platform works, and can prove it, not just pitch it. You will join a small, AI\-native disrupt squad within Autodesk’s Platform Services \& Emerging Technologies (PSET) organization, accountable for redefining how the platform is experienced, accessed, and built upon.
You won’t be handed a roadmap. You will identify high\-leverage opportunities, define what should exist, and demonstrate a dramatically better way through working proofs, using AI, real systems, and rapid experimentation.
Your role is not to produce designs and hand them off. On this team, product thinking, experience design, and engineering are rethinking how to work as an AI native delivery team. As the experience\-minded AI Builder, you bring deep experience and product design thinking into the what and the why, and you stay close enough to the build that your direction is grounded in something real. In practice, that means building AI\-assisted prototypes, shaping demos, and working directly with real flows and data yourself.
You do not maintain design specs or operate production systems. You are accountable for turning friction into opportunity and delivering working proofs that make a new experience credible and hard to dismiss.
Responsibilities
- Research how people actually work across the platform, using discovery interviews, journey mapping, and behavioral signals to surface the seams, bottlenecks, and handoffs that make it harder to use than it should be
- Define what should exist, turning research insights into a clear experience direction and prioritizing the few opportunities where a better interaction model creates outsized value for customers and the business
- Decide what to challenge: actively question whether existing flows, patterns, and interaction models should be replaced, simplified, or significantly improved, and use usability testing and experimentation to settle it on evidence rather than opinion
- Prove it: partner with PMs and developers, and get hands\-on yourself with AI tools, prototyping tools, and real content and data, to build working, testable prototypes that show the experience holds up with real users, not just that it could
- Package the results as clear “before vs after” proof points, grounded in user evidence, that make friction visible and the better experience undeniable, creating pull for change across teams
- Translate what the research and proofs reveal into direction: the interaction patterns and experience the platform should adopt next, and a viable path to get there
Minimum Qualifications
- 5\+ years driving experience and product design in complex, technical environments, with a strong track record of using prototyping and testing to discover, validate, and evolve solutions
- Acts with agency in ambiguous spaces, setting direction and making progress before anyone hands them a plan
- Strong design judgment: prioritizes the experience changes that create real value across a workflow, not just within a single screen or feature
- Strong craft across interaction design, information architecture, and end\-to\-end flows, including designing for self\-serve and for human plus AI interaction
- Hands\-on comfort with AI\-enabled design and prototyping tools, using them to build and pressure\-test experiences, not only to inform specs
- Comfortable operating across product, engineering, and experience, shaping solutions end\-to\-end rather than handing off between functions
- Background in workflow\-oriented or systems design rather than feature\-only or purely visual design
- Turns problems and insight into tangible, working experiences, whether prototypes or demos, not just mockups, flows, or specs
- Ability to synthesize user needs, business context, and technical constraints into a clear experience direction
- Ability to influence stakeholders and build alignment across teams without relying on formal authority
- High learning velocity and comfort operating in ambiguous, fast\-evolving problem spaces
Preferred Qualifications
- Experience working on 01 experiences, ideally in workflow\-heavy enterprise products or greenfield SaaS
- Designed for AI\-enabled products, including patterns for human plus AI interaction
- Familiarity with design systems, interaction patterns, and guardrails
- Exposure to evaluative and usability research, and using outcomes to guide decisions
\-
26WD100467, AI Builder, Concepteur principal d'expérience utilisateur
Aperçu du Poste
Ce poste s'adresse à un responsable de l'expérience utilisateur qui souhaite transformer en profondeur le fonctionnement de la plateforme et qui est capable de le prouver, et non pas seulement d'en faire la promotion. Vous rejoindrez une petite équipe innovante, spécialisée dans l'IA, au sein de l'organisation Platform Services \& Emerging Technologies (PSET) d'Autodesk. Vous serez chargé(e) de redéfinir la manière dont la plateforme est perçue, accessible et développée.
On ne vous remettra pas de feuille de route toute faite. Vous identifierez les opportunités à fort impact, définirez ce qui devrait exister et démontrerez une approche nettement plus efficace grâce à des preuves de concept, en utilisant l’IA, des systèmes réels et une expérimentation rapide.
Votre rôle ne consiste pas à produire des conceptions pour ensuite les transmettre à d’autres. Au sein de cette équipe, la réflexion produit, la conception d’expérience et l’ingénierie repensent la manière de travailler en tant qu’équipe de développement native de l’IA. En tant que développeur IA axé sur l’expérience, vous apportez une expertise approfondie et une approche de conception produit pour définir le « quoi » et le « pourquoi », tout en restant suffisamment proche du développement pour que vos orientations s’appuient sur des éléments concrets. Concrètement, cela implique de créer des prototypes assistés par l’IA, de mettre au point des démonstrations et de travailler vous\-même directement avec des flux et des données réels.
Vous ne gérez pas les spécifications de conception ni les systèmes de production. Vous êtes chargé(e) de transformer les frictions en opportunités et de fournir des preuves de concept fonctionnelles qui rendent une nouvelle expérience crédible et difficile à ignorer.
Responsabilités
- Étudier la manière dont les utilisateurs travaillent réellement sur la plateforme, à l’aide d’entretiens exploratoires, de cartographie des parcours et de signaux comportementaux, afin de mettre en évidence les ruptures, les goulots d’étranglement et les transferts qui rendent l’utilisation plus difficile qu’elle ne devrait l’être
- Définir ce qui devrait exister, en transformant les conclusions de la recherche en une orientation claire pour l’expérience utilisateur et en donnant la priorité aux quelques opportunités où un meilleur modèle d’interaction crée une valeur exceptionnelle pour les clients et l’entreprise
- Décider ce qu’il faut remettre en question : se demander activement si les flux, schémas et modèles d’interaction existants doivent être remplacés, simplifiés ou considérablement améliorés, et recourir à des tests d’utilisabilité et à l’expérimentation pour trancher sur la base de preuves plutôt que d’opinions
- Le prouver : collaborer avec les chefs de produit et les développeurs, et mettre vous\-même la main à la pâte avec des outils d’IA, de prototypage, ainsi que du contenu et des données réels, afin de construire des prototypes fonctionnels et testables qui démontrent que l’expérience tient la route avec de vrais utilisateurs, et pas seulement qu’elle pourrait le faire
- Présentez les résultats sous forme d’arguments clairs de type « avant/après », fondés sur des données utilisateur, qui mettent en évidence les frictions et rendent l’amélioration de l’expérience indéniable, suscitant ainsi une dynamique de changement au sein des équipes
- Traduisez les conclusions de la recherche et des preuves en orientations concrètes : les modèles d’interaction et l’expérience que la plateforme doit adopter à l’avenir, ainsi qu’une feuille de route viable pour y parvenir
Qualifications Minimales
- Au moins 5 ans d’expérience en pilotage et en conception de produits dans des environnements techniques complexes, avec une solide expérience dans l’utilisation du prototypage et des tests pour découvrir, valider et faire évoluer des solutions
- Capacité à agir de manière autonome dans des contextes ambigus, en définissant une orientation et en faisant avancer les choses avant même qu’un plan ne lui soit fourni
- Excellent jugement en matière de conception : donne la priorité aux changements d’expérience qui créent une réelle valeur tout au long d’un flux de travail, et pas seulement au sein d’un seul écran ou d’une seule fonctionnalité
- Maîtrise approfondie de la conception d’interactions, de l’architecture de l’information et des flux de bout en bout, y compris la conception d’expériences en libre\-service et d’interactions entre l’humain et l’IA
- Aisance pratique avec les outils de conception et de prototypage basés sur l’IA, en les utilisant pour créer et tester les expériences en conditions réelles, et pas seulement pour établir des spécifications
- Aisance à travailler à la croisée des domaines produit, ingénierie et expérience utilisateur, en façonnant des solutions de bout en bout plutôt qu’en se contentant de passer le relais entre les fonctions
- Expérience en conception orientée flux de travail ou en conception de systèmes, plutôt qu’en conception axée uniquement sur les fonctionnalités ou purement visuelle
- Capacité à transformer les problèmes et les insights en expériences tangibles et fonctionnelles, qu’il s’agisse de prototypes ou de démos, et non pas seulement de maquettes, de flux ou de spécifications
- Capacité à synthétiser les besoins des utilisateurs, le contexte métier et les contraintes techniques pour définir une orientation claire de l’expérience
- Capacité à influencer les parties prenantes et à créer une cohésion entre les équipes sans s’appuyer sur une autorité formelle
- Grande capacité d’apprentissage et aisance à évoluer dans des contextes problématiques ambigus et en constante évolution
Qualifications Souhaitées
- Expérience dans la création d’expériences « 01 », idéalement au sein de produits d’entreprise à forte intensité de flux de travail ou de solutions SaaS entièrement nouvelles
- Conception de produits basés sur l’IA, y compris des modèles d’interaction entre l’humain et l’IA
- Maîtrise des systèmes de conception, des modèles d’interaction et des garde\-fous
- Expérience en matière de recherche évaluative et d’ergonomie, et capacité à utiliser les résultats pour orienter les décisions
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 $130,000 and $232,320\. 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.
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.
Are you an existing contractor or consultant with Autodesk?
Please search for open jobs and apply internally (not on this external site).
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Autodesk, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Autodesk AI Hiring
Autodesk has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span San Francisco, CA, US, CA, US.
Location Context
AI roles in San Francisco pay a median of $265,000 across 1,335 tracked positions. That's 23% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.