Search for Machine Learning Engineer roles in Pasadena, CA, requiring 3+ years of experience, with a focus on computer vision, and company size as large.

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Machine Learning Engineer

Pasadena, CA

3 years + Experience

computer vision

Large

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Machine Learning Engineer role at the AWS Center for Quantum Computing is fundamentally about enhancing the quality assurance processes within quantum device manufacturing through advanced machine learning techniques, particularly focusing on optical defect detection. This position is crucial as it directly impacts the efficiency and reliability of quantum technologies, which are at the forefront of AWS’s innovation strategy. Key responsibilities include developing machine learning models, collaborating with scientists and engineers, and proposing scalable solutions that leverage emerging technologies in Generative AI. Success in this role requires not just technical proficiency but also a proactive approach to problem-solving and a strong understanding of the integration of machine learning within production environments. Candidates will need to demonstrate an ability to work effectively in a team, translating complex scientific data into actionable metrics while ensuring the stability and quality of software solutions.

Company Analysis:

Amazon Web Services (AWS) occupies a leadership position in the cloud computing industry, recognized for its comprehensive offerings and innovative solutions that cater to a wide range of businesses globally. The company fosters a culture of innovation and inclusivity, which is reflected in its emphasis on diverse experiences and continuous learning. The work environment appears fast-paced and collaborative, encouraging teamwork among engineers and scientists to push the boundaries of technology, particularly in the emerging field of quantum computing. This role is positioned within the Device Lifecycle software development team, indicating that the candidate will be part of a highly specialized group focused on scaling quantum technologies. As AWS continues to evolve and lead in cloud services, the machine learning engineer’s contributions will be crucial to meeting the strategic goals of maintaining high-quality standards and accelerating product innovation. Given AWS's emphasis on work-life balance and inclusive culture, candidates should feel supported in their professional development while contributing to groundbreaking projects.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Tell me about a time when you had to develop a machine learning model for a complex problem. What was your approach and what were the results?
Describe an experience where you had to troubleshoot a software deployment issue in a production environment. How did you resolve it?
Can you provide an example of how you've collaborated with scientists or researchers to achieve a project goal? What challenges did you face?
How do you prioritize tasks when managing different projects with overlapping deadlines?
Explain your experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation. How have you used these tools in your past projects?
What steps would you take to implement a machine learning model for optical defect detection in production?
In the context of developing an active learning pipeline for model performance improvement, how would you leverage human feedback?
Imagine you are working on a project that requires a significant collaboration with a cross-functional team. How would you ensure all stakeholders are aligned?
Why are you interested in the Machine Learning Engineer position at AWS, specifically within the Center for Quantum Computing?
How do your values align with AWS's mission and culture, as indicated by their emphasis on inclusivity and professional growth?
What emerging technologies in Generative AI do you believe will have the most significant impact on quantum computing and why?
How would you handle a situation where you identify a critical bug in a machine learning model just before it is launched into production?
What questions do you have about the team or the specific projects you would be working on within the Device Lifecycle team?
Can you describe a scenario where you successfully implemented a new process or tool that improved the efficiency of your team?

Job Details

Overview Company

Machine Learning Engineer

$129.3k/y-$223.6k/y

Amazon Web Services (AWS)

16 hours ago

Highlight

OnsiteFull-time3+ yearsMid

Summary

Amazon Web Services (AWS) is seeking a Machine Learning Engineer - Automated Optical Inspection to join their Center for Quantum Computing in Pasadena, CA. The role involves developing optical defect detection ML models to enhance quality assurance and accelerate device manufacturing.

About the Role

As a Machine Learning Engineer, you will develop and maintain platforms for ML model deployment, work with scientists and engineers to understand data, and implement design proposals. You will take ownership of software stability and quality, contributing to quantum computing technologies. You will also work on projects like developing ML vision models for optical defect detection and establishing active learning pipelines.

About You

Required:

Experience working in production ML environments, including deploying computer vision models.
Experience developing automation to solve problems at scale.
3+ years of non-internship professional software development experience.
2+ years of non-internship experience in system design, including design patterns, reliability, and scaling aspects.

Preferred:

MSc or PhD in a STEM discipline.
3+ years of full software development life cycle experience.
Experience working with scientists in a research environment.
Experience with Infrastructure as Code (IaC) tools such as Terraform, Cloudformation, or AWS CDK.
Experience deploying and maintaining Retrieval-Augmented Generation (RAG) models with generative AI.

Benefits

Base pay ranging from $129k–$223k depending on market location and experience.
Equity, sign-on payments, and other forms of compensation may be provided.
Full range of medical, financial, and other benefits.

Amazon Web Services (AWS)

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost.

Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.

Pasadena, CA