Remote AWS ML Cloud engineer jobs at U.S. companies

At Turing, we are looking for experienced AWS/ML cloud engineers who will be responsible for optimizing existing ML systems along with setting up, maintaining, and evolving the AWS cloud infrastructure of web applications. Here’s your chance to accelerate your career while working with top U.S. companies.

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Job description

Job responsibilities

  • Design and develop data-centric infrastructure tools
  • Facilitate and enhance real-time data analytics and research
  • Design and implement next-gen ML workloads, focusing on modern, efficient technologies
  • Help incorporate industry best practices and monitor system performance
  • Define and automate efficient workflows for software and ML development teams
  • Design and implement cost-effective migration strategies to the cloud
  • Configure and maintain cloud infrastructure components like security and networking services
  • Build and maintain AWS test instances, debug reported problems, and collaborate with other developers to better understand the product

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science, IT (or equivalent experience)
  • 3+ years of professional experience in AWS, ML, and Cloud engineering (rare exceptions for highly skilled engineers)
  • Working knowledge of programming languages such as Python, Java, R, SQL, etc.
  • Experience working with ML, cloud, and data pipelines
  • Knowledge of software/ML development life cycle, practices, CI/CD methodologies, and relevant tools
  • Experience with AWS deployments and relevant AWS services (eg. S3, ECS/EKS, CloudWatch)
  • Fluency in English to collaborate with engineering managers
  • Work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Strong understanding of CS fundamentals such as data structures and algorithms, computability, complexity, computer architecture, etc.
  • Experience working with third-party libraries for ML such as Scikit-Learn, TensorFlow, Keras, PyTorch, etc.
  • Experience with modern build strategies, continuous integration, unit testing, and TDD
  • Ability to quickly and independently learn new technologies, frameworks, and algorithms
  • Experience in building data pipelines and using tools and frameworks such as Spark, Hadoop, etc.
  • Proficiency with scripting languages (Bash/Python/Groovy)
  • Understanding of microservice software architecture, deployments, and relevant technologies

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How to Become an AWS/ML Developer?

Amazon Web Services (AWS) is a comprehensive and ever-evolving cloud computing platform. Infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS) are all services offered by AWS. AWS services may also provide a corporation with processing power, database storage, and content delivery services, among other things.

Amazon Web Services (AWS) was formed in 2006 as an expansion of's internal infrastructure for supporting its online retail activities. AWS was one of the first companies to provide a pay-as-you-go cloud computing model, which scales up to provide users with as much processing, storage, or throughput as they require.

What is the scope of AWS/ML development?

The AWS machine learning lets you predict accurately and gives better insights into data, while decreasing operational overhead to improve user experience. With the most complete collection of artificial intelligence (AI) and machine learning (ML) services, infrastructure, and implementation tools, AWS can assist you at every level of your ML adoption journey.

Certifications in Amazon Web Services (AWS) give doors to many of the highest-paying jobs. It aids you in overcoming the dangers of unstable employment. If you have an AWS certification, you may apply for a range of jobs. The following are the top employment roles based on your AWS certification:

  • AWS Cloud Architect: AWS Cloud Architect works as a connector between stakeholders and technical leadership, communicating directly with engineers as well as clients. Implementation efforts and technical designs are led by cloud architects, who ensure that new technologies are inserted.
  • Cloud developer: Cloud developers are in charge of developing corporate software applications and solutions. If you have experience with software development and a thorough grasp of the AWS platform, you may apply for a variety of AWS opportunities. Your job as a cloud developer will also benefit from AWS certification.
  • Cloud DevOps engineer: In addition to programming, a DevOps engineer is knowledgeable in network operations and system deployment. As a result, a diversity of talents paired with in-depth knowledge and hands-on experience on the AWS platform might lead to a number of job opportunities. Furthermore, having demonstrated your ability through AWS certification roughly quadruples your chances of securing an AWS job.
  • Cloud software engineer: If you're a software developer who works in Python, Ruby, JavaScript, or C++, Amazon Web Services offers a fantastic opportunity to advance your career. Your ability to design, build, and deploy systems/software on the Amazon Web Services platform will improve your chances of landing an AWS employment. So, obtain an AWS certification to prove your software design and development skills and stand out in the workforce.

What are the roles and responsibilities of an AWS/ML developer?

The following responsibilities are carried out by AWS developers:

  • Understanding an organization's current application architecture and providing feedback and/or suggestions to enhance or change it
  • Defining and documenting best practices and methodologies for app deployment and infrastructure maintenance
  • Moving web apps to AWS with the help of the IT team or department.
  • Developing, testing, and implementing low-cost migration strategies
  • Developing reusable, effective, and scalable programs
  • Analyzing, testing, troubleshooting, and upgrading software to ensure that applications run on all web browsers.
  • Using numerous AWS services like APIs, RDS instances, and Lambda to build a serverless application.
  • Examining and assessing programs in order to detect technical faults and give recommendations and/or remedy proposals.

How to become an AWS/ML developer?

A basic understanding of traditional IT-related courses is required to begin a career in AWS. It's crucial to have a thorough grasp of cloud computing, as well as the confidence to learn how to use it properly.

Learning AWS requires knowledge of hardware and software configuration, advanced networking skills, server setup, performance tweaking capabilities, operating system memory management, application deployment utility, and database or data source configuration.

Learning how to use AWS Machine Learning tools and services is a sensible business strategy. Both professionals and corporate units will benefit from this. This qualification is most valuable for specialists, although it may also be obtained by a new professional. It is beneficial for people who have some expertise in creating, delivering, and maintaining machine learning solutions for a variety of business challenges. Furthermore, professionals in development or data science would benefit greatly from this test.

The AWS Certified Machine Learning Specialist Beta Exam is required to enter this career sector. Amazon provides this service (AWS). Furthermore, there is no requirement to participate in this program in order to obtain the AWS ML Specialist certificate. With the passage of time, AWS' credentials have grown far more versatile and cost-effective.

Also, make sure to include all relevant qualifications and achievements in your AWS/ML cloud developer resume. This will help recruiters quickly understand your capabilities and get shortlisted for openings.

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Skills required to become an AWS/ML developer

1. Deployment

As an AWS developer, one of the most essential and in-depth skills to have is the ability to deploy web apps to AWS. Not only are there a variety of ways to deploy to AWS, but they're also continually changing as new approaches emerge and older ones go away. As a result of this change, the following list of AWS deployment methodologies should be double-checked to make sure no fresh options are available.

To begin, you should be familiar with the manual method of deploying a web application to Amazon Elastic Compute Cloud (EC2) servers. You'll be able to build on this foundation and maybe create your own automated deployment methods once you understand it.

Following that, you should be familiar with CloudFormation and know how to use it to not only deploy but also to construct your application architecture. Elastic Beanstalk and its many services should also be recognizable to you. Although opinions differ on whether EB is the best or worst service for delivering programs to AWS, it is extensively used, therefore familiarity with it is necessary.

Finally, as the use of containers grows, knowing how to deploy programs using Elastic Container Service (ECS) for Docker or Elastic Kubernetes Service (EKS) for Kubernetes becomes more crucial.

2. Security

At times, AWS's power might be a double-edged sword. It gives you a lot of freedom, but it doesn't hold your hand. Self-sufficiency is essential, as is a thorough understanding of the AWS Security Model and IAM. The most common issues and challenges in AWS are typically caused by developers' lack of understanding of IAM. Understanding how Roles and Policies work will assist you in every part of your AWS employment.

The management of secrets is another tricky problem that comes up regularly. Last year, AWS launched a new tool called Secrets Manager, which streamlines the process of storing and retrieving sensitive data in your online projects (such as API keys, passwords, and so on).

3. SDK for AWS

The AWS Software Development Kit (SDK) is the code that enables your app to interact with AWS. The SDK's API layer is massive; even if you're an expert, there are constantly new things you can do with it. Knowing the SDK will save you time since connecting with AWS will be second nature to you. It's common for developers to be unclear where to start when obtaining an item from an S3 bucket or connecting to a DynamoDB database. Don't be a coder like that. Learn how to use one of the world's most powerful technologies by getting some SDK experience.

4. Databases

Databases are an important part of every online service, and AWS has numerous options to suit that demand. The problem is figuring out which database service is suitable for your project. If you don't understand all of the options and some of the pros and cons, you risk choosing the wrong solution and hindering the growth of your application.

5. Debugging

If you're a developer, you know how frustrating it may be to run into a roadblock. You're undoubtedly also aware of how much easier it is to overcome obstacles once you've overcome them. In this regard, AWS is no exception. Every time you use AWS to solve a problem, it makes troubleshooting and fixing the next one a lot easier.

Unfortunately, there is no roadmap for debugging. It's simply a matter of getting in and gaining AWS experience. Although the bulk of your problems will be caused by IAM permissions or VPC-based access limits (such as Security Groups), there's no replacement for going into the platform and developing. You'll come into issues and have to figure out how to solve them. Think about your experience the next time you have an issue and how to properly troubleshoot it.

Interested in remote AWS/ML developer jobs?

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How to get AWS/ML developer jobs?

AWS/ML engineers must work hard enough to keep up with all of the industry's current advancements and to steadily expand their talents. They must effectively and continuously follow the best practices in their sector to flourish. There are two things that developers should consider moving ahead in this regard. While practicing, they may seek assistance from someone who is more experienced and adept at teaching new skills. You must also fine-tune your analytical, computer programming, and soft abilities as an AWS/ML Developer. As a result, the designers must ensure that someone is available to assist them.

Turing offers the best remote AWS/ML development opportunities to enhance your career as an experienced AWS/ML developer. Working on difficult new technology and business challenges can assist you in growing rapidly. Join our network of the world's best developers to find long-term, full-time remote AWS development jobs with higher compensation and promotion possibilities.

Why become an AWS/ML developer at Turing?

Elite US jobs
Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Career growth
Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community
Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.
Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home
Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top US firms from the comfort of your home.

Great compensation
Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their AWS/ML developers?

Every AWS/ML developer at Turing can choose their preferred pricing. Turing, on the other hand, will propose a salary at which we are certain we can find you a successful and long-term position. Our suggestions are based on our analysis of market conditions as well as customer preferences.

Frequently Asked Questions

We are a Palo Alto-based 'deep' jobs platform allowing talented software developers to work with top US firms from the comfort of their homes. We are led by Stanford alumni and successful A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Currently, we have openings only for the developers because of the volume of job demands from our clients. But in the future, we might expand to other roles too. Do check out our careers page periodically to see if we could offer a position that suits your skills and experience.

It is the combination of our core business model and values that makes us different from others. We provide full-time, long-term projects to remote developers whereas most of our competitors offer more freelance jobs.

No, the service is absolutely free for software developers who sign up.

Ideally, a remote developer needs to have at least 3 years of relevant experience to get hired by Turing, but at the same time, we don't say no to exceptional developers. Take our test to find out if we could offer something exciting for you.

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In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

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