Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

Amazon

World's most comprehensive and broadly adopted cloud platform, pioneering cloud computing and continuous innovation.

Arlington, VA, USA • Herndon, VA 20170, USA

Machine Learning

Mid-Level Software Engineer

In-Person

5,000+ Employees

3+ years of experience

AI · Enterprise SaaS · Healthcare

Description For Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

AWS US Federal Professional Services is seeking a Computer Vision engineer to develop enterprise-scale ML solutions. This role focuses on collaborating with scientists and engineers to create computer vision and remote sensing capabilities for public sector entities, medical centers, and non-profits. The position involves working with various imagery types including satellite imagery, medical imaging, aerial video, and X-Ray data.

The role requires working with massive datasets and implementing scalable computer vision systems. You'll be part of AWS's extensive ML community, developing cutting-edge solutions for enterprise-scale applications. This customer-facing position involves architecting and implementing innovative, AWS Cloud-native ML solutions while guiding teams and helping customers adopt AWS ML capabilities.

Key aspects include delivering end-to-end ML projects, implementing MLOps workflows, and working with TB-scale datasets. You'll collaborate with Professional Services Data Scientists, Cloud Architects, and customer teams to build secure, robust solutions. The position requires TS/SCI security clearance and offers opportunities for growth in AWS's inclusive culture.

AWS values diverse experiences and maintains a strong focus on work-life harmony. The company provides extensive career development resources, mentorship opportunities, and fosters an inclusive environment through employee-led affinity groups and ongoing learning experiences. Join AWS to be part of a team that's continuously innovating and helping customers achieve their mission goals through advanced ML solutions.

Last updated 3 months ago

Responsibilities For Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

Engage directly with customers to understand business problems and implement ML solutions
Deliver Machine Learning projects from beginning to end
Implement Machine Learning Operations (MLOps) workflows
Work on TB scale datasets, creating scalable computer vision systems
Collaborate with Cloud Architects to build secure, robust cloud-native ML solutions
Work with customer account teams, scientific research teams and product engineering teams

Requirements For Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

Python

Java

Bachelor's degree in computer science or equivalent
3+ years of designing or architecting experience
3+ years professional experience with enterprise programming applications and Linux
2+ years of cloud software development experience
Current, active US Government Security Clearance of TS/SCI or above

Benefits For Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

Flexible work hours
Mentorship opportunities
Career development resources
Employee-led affinity groups
Inclusive work culture

Amazon

World's most comprehensive and broadly adopted cloud platform, pioneering cloud computing and continuous innovation.

Arlington, VA, USA • Herndon, VA 20170, USA

Machine Learning

Mid-Level Software Engineer

In-Person

5,000+ Employees

3+ years of experience

AI · Enterprise SaaS · Healthcare

Amazon

What are the time complexities of quicksort, mergesort, and other sorting algorithms?

Data Structures & AlgorithmsMedium

What are the time complexities of different sorting algorithms, such as quicksort and mergesort? Explain the best, average, and worst-case scenarios for each, and provide examples of when you might choose one algorithm over another. Additionally, discuss the space complexity of each algorithm.

Arrays

Database Problems

Amazon

How would you implement a service like Twitter?

System DesignHard

Let's design a Twitter-like service. Consider the following: Core Functionality: How would you implement the ability for users to post tweets, follow other users, and view a timeline of tweets from the users they follow? Data Model: What database schema would you use to store tweets, user information, and follower relationships? Consider scalability and efficiency for reads and writes. Scalability: How would you handle a large number of users and tweets? Discuss strategies for sharding, caching, and load balancing. Real-time Updates: How would you ensure that users see new tweets in their timeline in near real-time? Consider using technologies like WebSockets or Server-Sent Events. Search: How would you implement a search feature that allows users to find tweets containing specific keywords or hashtags? Think about indexing strategies and search algorithms. Rate Limiting: How would you prevent abuse and ensure fair usage of the service? Describe your approach to rate limiting API requests. Example Scenario: Imagine a user, Alice, follows 1,000 other users, including Bob. Bob posts a tweet. Explain how that tweet would propagate to Alice's timeline, considering potential performance bottlenecks. Technology Stack: What technologies (programming languages, frameworks, databases, etc.) would you choose and why?

Database Problems

Graphs

Arrays

Strings

Amazon

Tell me about a time you disagreed with a colleague and how you resolved it.

Behavioral

Tell me about a time you disagreed with a colleague. What was your approach to resolving the disagreement, and what was the outcome? How did you ensure that your interaction remained professional and respectful, even with differing viewpoints? For example, imagine you're working on a new feature for an e-commerce platform. You believe that a simplified checkout process will lead to higher conversion rates, while your colleague argues that adding more security steps is crucial, even if it adds friction for the user. Describe the situation, your reasoning, your colleague's reasoning, and the steps you took to reach a resolution that benefited the project and maintained a positive working relationship. What did you learn from this experience?

Interested in this job?

Jobs Related To Amazon Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

Software Engineer- AI/ML, AWS Neuron Machine Learning Distributed Training, ML Accuracy

Amazon

AWS Neuron seeks ML Engineer to develop distributed training solutions for large language models using PyTorch, TensorFlow, and JAX on custom silicon.

Software Engineer- AI/ML, AWS Neuron

Amazon

AWS Neuron ML Engineer role focusing on distributed training and optimization of large language models using AWS Inferentia and Trainium accelerators.

Software Development Engineer, Finance Technology

Amazon

Build AI/ML applications for Amazon's finance systems, focusing on data processing, forecasting, and automation within the FinTech team.

Machine Learning Engineer, MLE II, Amazon Q in QuickSight

Amazon

Machine Learning Engineer role at Amazon working on Q in QuickSight, focusing on LLMs and NLP for business intelligence solutions.

Software Development Engineer, SageMaker Training Platform

Amazon

Software Development Engineer position at Amazon's SageMaker Training Platform, building and scaling machine learning infrastructure.