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Causal Inference Machine Learning Postdoctoral Jobs in Oregon

Amerilife Group, LLC

OR

Technical Requirements Statistics & Machine Learning Required * Strong foundation in statistical ... causal inference * Experience optimizing models for business ROI; exposure to reinforcement ...

Honor

Staff Data Scientist

Portland, OR · Remote

You possess a strong foundation in traditional predictive machine learning (e.g., classification ... Experience designing experiments and applying causal inference methods to rigorously determine ...

BlueLabs, Inc.

OR · On-site

Expertise building predictive models using regression and machine learning techniques * Ability to ... Knowledge of experimental design and causal inference * Experience creating and delivering ...

Netflix

OR · On-site

$523K - $920K/yr

The team builds causal inference and predictive models to quantify such impact to members, and use ... Responsibilities Hire, inspire, and grow high-performing Machine Learning Scientists, Data ...

Nvidia

OR

$122K - $161K/yr

Expertise in inference engines like vLLM and SGLang * Expertise in machine learning compilers (e.g. Apache TVM, MLIR) * Open source project ownership or contributions Your base salary will be ...

HiddenLayer

AI Red Teamer

OR · On-site +1

Deep understanding of attack techniques specific to machine learning and artificial intelligence systems (data poisoning, inference attacks, model injection, prompt injection, jailbreaking, etc.

WEKA

OR · On-site

$126K - $166K/yr

It transforms legacy data silos into data pipelines that dramatically increase GPU utilization and make AI model training and inference, machine learning, and other compute-intensive workloads run ...

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Causal Inference Machine Learning Postdoctoral information

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Oregon? For Causal Inference Machine Learning Postdoctoral jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Oregon look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Oregon are:
What cities in Oregon are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in Oregon with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Senior Machine Learning Engineer, MLOps West Coast

Senior Machine Learning Engineer, MLOps West Coast

Autodesk

Portland, OR

$131K - $235K/yr

Full-time

Posted 9 days ago

Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

6th of 209 rated software companies

Job description

Job Requisition ID #

26WD96432

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.

As aSeniorMachine LearningEngineerfocused on Machine Learning Ops (MLOps) for CAD and BIM, you will ensure AI-powered experiences meet high standards for reliability, scalability, and operational excellence across Autodesk products. You will build and operate the infrastructure that takes models from development into production, including deployment automation, monitoring, and secure, scalable service integration. You will partner closely with researchers, evaluation engineers, and product teams to translate evaluation requirements into production quality gates, reduce operational risk, and continuously improve model performance in real customer environments.

You will report to a manager in the Model Delivery team within Autodesk Research. This role is based in proximity to our North American west coast offices, including San Francisco, Portland, and Vancouver. We support both in-person, hybrid, and remote work.

Responsibilities

  • Test and Deploy Production Models:Automate model testing and validation. Implement and operate CI/CD pipelines to enable safe, repeatable deployments and rollbacks.
  • Operate Inference Services:Provision and manage backend resources for inference (compute, containers, scaling), and tune performance, reliability, and cost in production.
  • Monitor Model Health and Performance:Define and continuously monitor health and performance metrics for deployed services. Triage issues by severity and drive timely resolution, including incident response and runbooks.
  • REST API Integration:Own end-to-end REST API integration, connecting backend model services to product and platform surfaces through scalable, containerized services.
  • Product Ownership and Cross-functional Collaboration:Work with researchers, evaluation engineers, product managers, and partner engineering teams to deliver production-ready solutions, communicate status and risks, and escalate when needed.

Minimum Qualifications

  • BS or MS in Computer Science, Computer Engineering, or equivalent industry experience.
  • 3+ years of professional software engineering experience building and operating production services.
  • Experience automating testing and deployments using CI/CD, including release workflows that support safe rollouts and rollbacks.
  • Experience building and operating cloud hosted, containerized services (for example Docker and Kubernetes or similar), including provisioning resources and scaling inference workloads.
  • Experience building REST APIs using Python based frameworks (or similar), and integrating backend services with product or platform consumers.
  • Strong software engineering fundamentals: version control, code quality, and writing maintainable, testable software.
  • Strong written communication skills to document architectures, runbooks, and operational processes.

Preferred Qualifications

  • Experience running production ML or LLM inference services, including performance tuning, cost optimization, and capacity planning.
  • Experience with observability tooling and practices (metrics, logging, tracing, alerting) and incident response in an on-call environment.
  • Experience deploying services within an enterprise internal platform environment with standardized pipelines, security controls, and compliance requirements.
  • Familiarity with rate limiting, authentication and authorization, and API security best practices.
  • Familiarity with design, manufacturing, or AEC workflows, and how backend services integrate into CAD/BIM product experiences.
  • Familiarity with Agile or Scrum ways of working.

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!

Salary transparency

Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $131,400 and $235,950. 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.Salary is one part of Autodesk's competitive compensation package. For Canada based roles, we expect a starting base salary between $123,000 and $180,400. 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

Are you an existing contractor or consultant with Autodesk?

Please search for open jobs and apply internally (not on this external site).

What Autodesk employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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