2

Remote Director Machine Learning Jobs in Washington

Remote - Patent Attorneys

Fairfax, VA · Remote

$280K - $350.03K/yr

... such as AI, Machine Learning, Cloud, Wireless and Data Storage. This role offers full remote ... Collegial team culture with direct partner and client interaction; Transparent, competitive ...

Remote - Patent Agents

Fairfax, VA · Remote

$280K - $350.03K/yr

... such as AI, Machine Learning, Cloud, Wireless and Data Storage. This role offers full remote ... Collegial team culture with direct partner and client interaction; Transparent, competitive ...

At least three (3) years of direct experience in machine learning. * Must have a Advanced Degree ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

At least three (3) years of direct experience in machine learning. * Must have a Advanced Degree ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Remote(candidate needs to be based in the US preferablyCONUS) Reports to:President of Platforms ... Demonstrated success in integrating AI, machine learning, or agentic tools (e.g., autonomous agents ...

next page

Showing results 1-20

Remote Director Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Director of Machine Learning, and why are they important?

To thrive as a Remote Director of Machine Learning, you need advanced expertise in machine learning algorithms, data science, and leadership, typically supported by a graduate degree in a related field and extensive experience in deploying ML solutions. Familiarity with tools like Python, TensorFlow, PyTorch, cloud platforms, and experience with project management systems is essential, and certifications such as AWS Certified Machine Learning can be advantageous. Outstanding communication, strategic thinking, and the ability to mentor and manage distributed teams are crucial soft skills in this role. These skills and qualities are vital to successfully lead innovative ML projects, align technical teams with business goals, and drive impactful outcomes in a remote environment.

How does a Remote Director of Machine Learning typically coordinate and lead distributed teams across different time zones?

As a Remote Director of Machine Learning, effective coordination of distributed teams requires strong communication strategies, including regular video meetings, clear documentation, and use of collaborative project management tools. Leaders in this role often establish overlapping core hours and leverage asynchronous communication to accommodate various time zones. They focus on aligning goals, fostering a culture of transparency, and ensuring continuous progress through well-defined milestones. Building trust and maintaining team engagement remotely are common challenges, but successful directors prioritize mentorship, feedback, and virtual team-building activities to create a cohesive work environment.

What does a Remote Director of Machine Learning do?

A Remote Director of Machine Learning leads teams of data scientists and engineers to develop, implement, and oversee machine learning solutions for an organization, all while working remotely. They are responsible for setting the strategic direction for ML projects, collaborating with stakeholders, and ensuring that models align with business objectives. This role typically involves both technical leadership—such as reviewing algorithms and architectures—and managerial duties, such as mentoring staff and managing budgets. Working remotely, they use digital collaboration tools to communicate, monitor progress, and deliver results effectively.

What is the difference between Remote Director Machine Learning vs Remote Data Science Manager?

AspectRemote Director Machine LearningRemote Data Science Manager
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related field; experience in ML algorithmsMaster's in Data Science, Statistics, or related; strong analytical background
Work EnvironmentLeads ML teams, develops models, and oversees deployment in tech-focused companiesManages data science teams, focuses on insights and analytics for business decisions
Employer & Industry UsageTech firms, AI startups, large enterprises with AI initiativesFinancial, healthcare, retail, and other industries leveraging data insights

While both roles require advanced education and involve data-driven work, the Remote Director Machine Learning primarily focuses on leading ML model development and deployment, whereas the Remote Data Science Manager emphasizes managing data analysis teams and deriving business insights.

What are popular job titles related to Remote Director Machine Learning jobs in Washington? For Remote Director Machine Learning jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Remote Director Machine Learning jobs? Cities in Washington with the most Remote Director Machine Learning job openings:
Principal ML Engineer, Machine Learning Platform and Systems Architecture

Principal ML Engineer, Machine Learning Platform and Systems Architecture

Autodesk

Washington, DC • Remote

Full-time

Posted 23 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

5th of 183 rated software companies


Job description

Job Requisition ID #

26WD97132

26WD97132, Principal Machine Learning Engineer, ML Platform and Systems Architecture

French translation to follow!/Traduction francaise a suivre!

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 looking for a Principal ML Engineer, ML Platform and Systems Architecture to lead the design and evolution of large-scale machine learning platforms. In this role, you will own high-impact technical initiatives that span ML infrastructure,data systems, model lifecycle tooling, and production architecture. You will work closely with researchers, product teams, andengineering leadership to build the systems that bring advanced machine learning into reliable, scalable product experiences.This is a senior technical leadership role for an engineer who excels at system architecture, distributed computing, and end-to-end platform thinking. You will help define the technical direction for ML systems and drive execution across ambiguous, cross-functional, high-value initiatives.This role is fully remote-friendly, with team members distributed across the US and Canada.

Location: US or Canada Remote

Responsibilities

  • Lead architecture and delivery for major ML platform capabilities across training, evaluation, deployment, and observability

  • Design scalable systems for distributed training, data processing, feature and model lifecycle management, and production inference

  • Own platform-level technical outcomes from design through deployment, operations, and continuous improvement

  • Drive the design and scaling of data pipelines for large-scale structured and semi-structured technical datasets

  • Lead architecture for distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms

  • Establish strong practices for data lineage, provenance, governance, and responsible data usage in ML systems

  • Guide the design of model deployment, inference services, monitoring, and observability for production ML workloads

  • Contribute to the development of ML-ready representations for geometry, graph, hierarchical, or multimodal data

  • Clarify ambiguous problem spaces, define solution approaches, and lead execution across multiple engineers and teams

  • Establish and improve engineering standards, operational practices, and architectural patterns for ML systems

  • Lead incident response for critical platform issues and drive lasting improvements across system health and supportability

  • Mentor engineers and act as a force multiplier through design leadership, coaching, and technical reviews

  • Communicate technical strategy, tradeoffs, and execution plans clearly to technical and non-technical stakeholders

Minimum Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience

  • Typically 6 to 8 years of industry experience in software engineering, ML infrastructure, distributed systems, or platform engineering, including experience leading design and delivery of complex technical systems

  • Deep experience in software architecture, distributed systems, large-scale data platforms, or ML infrastructure

  • Strong proficiency in Python and strong command of production software engineering practices

  • Experience leading complex technical initiatives that span multiple engineers or cross-functional teams

  • Strong experience with large-scale data pipelines, distributed data processing, and cloud-native platform architectures

  • Experience with model deployment, inference systems, and production observability

  • Demonstrated ability to make architecture decisions that balance performance, scalability, reliability, and cost

  • Strong communication and stakeholder management skills

Preferred Qualifications

  • Experience building data governance, lineage, and provenance capabilities for ML platforms

  • Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data

  • Deep experience with distributed ML frameworks and large-scale training infrastructure

  • Experience with Kubernetes, workflow orchestration systems, and modern ML platform tooling

  • Experience with production incident leadership, service reviews, resiliency practices, and operational readiness

  • Familiarity with AEC data, computational design workflows, BIM/CAD ecosystems, or Autodesk products

The Ideal Candidate

  • Is a strong architect and hands-on engineer

  • Drives clarity and momentum in ambiguous spaces

  • Thinks at platform level and acts with strong product and business awareness

  • Raises the engineering bar for system design, quality, and operational excellence

  • Builds trust through technical depth, calm judgment, and execution leadership

______________________________________________________________________________________________________________

26WD97132, Ingenieur principal en apprentissage automatique, Architecture des plateformes et des systemes d'apprentissage automatique

Presentation du poste

Le travail que nous accomplissons chez Autodesk touche pratiquement chaque habitant de la planete. En creant des outils logiciels destines a la conception de batiments, de machines et meme des films les plus recents, nous influencons et donnons les moyens a certaines des personnes les plus creatives au monde de resoudre des problemes qui comptent.

Autodesk recherche un ingenieur principal en apprentissage automatique, architecture de plateformes et de systemes ML, pour diriger la conception et l'evolution de plateformes d'apprentissage automatique a grande echelle. A ce poste, vous serez responsable d'initiatives techniques a fort impact couvrant l'infrastructure ML, les systemes de donnees, les outils de gestion du cycle de vie des modeles et l'architecture de production. Vous travaillerez en etroite collaboration avec les chercheurs, les equipes produit et la direction technique pour construire les systemes qui transforment l'apprentissage automatique avance en experiences produit fiables et evolutives. Il s'agit d'un poste de direction technique senior destine a un ingenieur excellant dans l'architecture systeme, le calcul distribue et la reflexion sur les plateformes de bout en bout. Vous contribuerez a definir l'orientation technique des systemes d'apprentissage automatique et piloterez la mise en uvre d'initiatives ambigues, transversales et a forte valeur ajoutee. Ce poste est entierement compatible avec le teletravail, les membres de l'equipe etant repartis aux Etats-Unis et au Canada.

Lieu : Etats-Unis ou Canada (teletravail)

Responsabilites

  • Diriger l'architecture et la mise en uvre des principales fonctionnalites de la plateforme d'apprentissage automatique (ML) en matiere de formation, d'evaluation, de deploiement et d'observabilite

  • Concevoir des systemes evolutifs pour la formation distribuee, le traitement des donnees, la gestion du cycle de vie des caracteristiques et des modeles, ainsi que l'inference en production

  • Assumer la responsabilite des resultats techniques au niveau de la plateforme, de la conception au deploiement, en passant par l'exploitation et l'amelioration continue

  • Piloter la conception et la mise a l'echelle de pipelines de donnees pour des ensembles de donnees techniques structures et semi-structures a grande echelle

  • Diriger l'architecture des systemes de traitement et d'orchestration de donnees distribues tels que Ray, Airflow, Spark ou des plateformes similaires

  • Mettre en place des pratiques rigoureuses en matiere de tracabilite des donnees, de provenance, de gouvernance et d'utilisation responsable des donnees dans les systemes d'apprentissage automatique

  • Guider la conception du deploiement des modeles, des services d'inference, de la surveillance et de l'observabilite pour les charges de travail d'apprentissage automatique en production

  • Contribuer au developpement de representations pretes pour l'apprentissage automatique pour les donnees geometriques, graphiques, hierarchiques ou multimodales

  • Clarifier les problematiques ambigues, definir des approches de solution et diriger la mise en uvre en collaboration avec plusieurs ingenieurs et equipes

  • Etablir et ameliorer les normes d'ingenierie, les pratiques operationnelles et les modeles architecturaux pour les systemes d'apprentissage automatique

  • Diriger la gestion des incidents pour les problemes critiques de la plateforme et piloter des ameliorations durables en matiere de sante et de maintenabilite du systeme

  • Encadrer les ingenieurs et agir comme un multiplicateur de force par le biais du leadership en conception, du coaching et des revues techniques

  • Communiquer clairement la strategie technique, les compromis et les plans d'execution aux parties prenantes techniques et non techniques

Qualifications minimales

  • Licence ou master en informatique, ingenierie ou dans un domaine connexe, ou experience professionnelle equivalente

  • Generalement 6 a 8 ans d'experience professionnelle en genie logiciel, infrastructure ML, systemes distribues ou ingenierie de plateformes, y compris une experience dans la direction de la conception et de la mise en uvre de systemes techniques complexes

  • Experience approfondie en architecture logicielle, systemes distribues, plateformes de donnees a grande echelle ou infrastructure ML

  • Maitrise approfondie de Python et solide connaissance des pratiques d'ingenierie logicielle en production

  • Experience dans la direction d'initiatives techniques complexes impliquant plusieurs ingenieurs ou des equipes interfonctionnelles

  • Solide experience des pipelines de donnees a grande echelle, du traitement distribue des donnees et des architectures de plateformes cloud-native

  • Experience du deploiement de modeles, des systemes d'inference et de l'observabilite en production

  • Capacite averee a prendre des decisions architecturales qui concilient performances, evolutivite, fiabilite et cout

  • Solides competences en communication et en gestion des parties prenantes

Qualifications souhaitees

  • Experience dans la mise en place de capacites de gouvernance des donnees, de tracabilite et de provenance pour les plateformes d'apprentissage automatique

  • Experience dans la creation de representations pretes pour l'apprentissage automatique pour les donnees geometriques, graphiques, hierarchiques ou multimodales

  • Experience approfondie des frameworks d'apprentissage automatique distribues et des infrastructures de formation a grande echelle

  • Experience avec Kubernetes, les systemes d'orchestration de workflows et les outils modernes des plateformes d'apprentissage automatique

  • Experience dans la gestion des incidents en production, les revues de services, les pratiques de resilience et la preparation operationnelle

  • Connaissance des donnees AEC, des workflows de conception computationnelle, des ecosystemes BIM/CAO ou des produits Autodesk

Le candidat ideal

  • Est un architecte chevronne et un ingenieur de terrain

  • Apporte clarte et dynamisme dans des contextes ambigus

  • Pense a l'echelle de la plateforme et agit avec une forte conscience des produits et des enjeux commerciaux

  • Releve le niveau d'exigence en matiere d'ingenierie pour la conception des systemes, la qualite et l'excellence operationnelle

  • Instaure la confiance grace a ses connaissances techniques approfondies, son jugement serein et son leadership en matiere d'execution

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 $152,000 and $272,250. 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. Autodes...


Autodesk logo

About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982