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Remote AI/ML/Data engineer jobs

At Turing, top-tier clients are on the hunt for AI/ML/Data engineers who have experience working on a range of classification, prediction and optimization problems. The position will involve building models using machine learning techniques such as NLP and Neural Networks to power AI-based applications.

Check out the best jobs for October 2021here

Job description

Job responsibilities

  • Create products with great user experience in the domain of AI/ML
  • Understand the project, design an effective roadmap & manage overall project lifecycle
  • Use ML/AI principles to design & develop highly scalable models/classifiers/algorithms
  • Communicate & influence technical details of the projects & work with cross-functional teams
  • Create products with great user experience in the domain of AI/ML
  • Understand the project, design an effective roadmap & manage overall project lifecycle
  • Use ML/AI principles to design & develop highly scalable models/classifiers/algorithms
  • Communicate & influence technical details of the projects & work with cross-functional teams
  • Continuously integrate and ship code into the cloud environment
  • Collaborate with product managers to produce wire-frame mock-ups
  • Drive usability sessions to refine workflows, get buy-ins & move towards full implementation

Minimum requirements

  • Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
  • 3+ years of experience in either: AI, ML, Deep Learning or Natural Language Processing (exceptions for highly skilled devs)
  • Skilled in any general-purpose programming/query languages: Python, SQL, PHP, Java, C#
  • Fluency in English to collaborate with engineering managers
  • Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
  • 3+ years of experience in either: AI, ML, Deep Learning or Natural Language Processing (exceptions for highly skilled devs)
  • Skilled in any general-purpose programming/query languages: Python, SQL, PHP, Java, C#
  • Fluency in English to collaborate with engineering managers

Preferred skills

  • Knowledge of large systems, complex code bases, & version control systems like Git
  • Skilled at ML libraries, predictive modeling, pattern recognition, data mining, etc.
  • Experience with common data science toolkits, such as R, NumPy, MatLab etc.
  • Experience with ML frameworks (like Keras, PyTorch) & libraries (like Scikit-learn, NLTK)
  • Knowledge of large systems, complex code bases, & version control systems like Git
  • Skilled at ML libraries, predictive modeling, pattern recognition, data mining, etc.
  • Experience with common data science toolkits, such as R, NumPy, MatLab etc.
  • Experience with ML frameworks (like Keras, PyTorch) & libraries (like Scikit-learn, NLTK)
  • Proficiency in applied statistics: regression, distributions, statistical testing etc.
  • Deep understanding of Artificial Neural Networks and Deep Learning Frameworks
  • Skilled with Full Stack (FE & BE Development), Distributed & Parallel systems, etc.
  • Good command over algorithms, data structures, & computer science fundamentals
  • The ability to work full-time (40 hours/week) and a 4 hour overlap with US time zones
  • Function & find effective solutions to problems without hand-holding & micromanagement

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How to become an AI-ML engineer in 2021?

AI-ML engineers build, test, and deploy AI models, maintain the underlying AI infrastructure, as well as navigate between traditional software development and machine learning implementations.

AI-ML engineers focus on researching, planning, and producing self-running Artificial Intelligence systems to automate predictive models. AI-ML engineering jobs responsibilities also include designing and developing the AI algorithms competent of learning and making predictions that explain Machine Learning. It allows engineers not to rely on a series of steps, but learn from the data supplied into ML algorithms.

Remote AI-ML engineering jobs are seeing an exponential increase as more and more companies worldwide lean towards automation. If you have gained expertise and fine-tuned your AI-ML skills, you can become a top AI-ML engineer. AI-ML engineering offers the opportunity to bag a secure, high-paying remote job.

What is the scope in AI-ML engineering?

AI-ML engineering jobs offer career stability and various opportunities due to their high demand across industries. This profession has seen an exponential rise in job listings by over 300% between 2015 and 2018. And this number continues to grow as more and more organizations worldwide accomplish the potential of coupling big data with software.

While Artificial Intelligence is an umbrella term with various applications, obtaining the skills and specializing in particular areas take time and maturity. Rather than anything, prospective careers would necessitate a desire to be interested and take risks.

As different industries are always in demand for highly-skilled AI-ML engineers, AI-ML engineering jobs listings are rarely empty. These engineers are the best problem solvers who create, test, and execute numerous AI models. They are also involved in the creation and management of self-operating applications that promote ML projects.

What are the roles and responsibilities of AI-ML engineers?

AI-ML engineer’s responsibilities on the team include multifarious tasks, like -

  • making a Machine Learning algorithm to capture the whiteboard sketches of website layouts drawn by the UX team in order to produce finished website layouts for the Software development team. If executed successfully, this workflow will help companies save a lot on man-hours, and accelerate the feedback loops related to website UX improvements.

  • accumulating data from multiple HotJar users and driving it against ML algorithms to find frequent pitfalls and roots to user distraction. With the right data analysis, companies can find user distraction patterns like how, when, and why.

  • creating a model connecting HotJar and A/B testing data with the Google Analytics data and information. It will help in creating improved layouts, which will raise the time spent on the site, higher customer acquisition, etc.

  • predicting the success of various layouts recommended by the UX team.

Besides these, there might be more to the role and responsibility of an AI-ML engineer. As this field is still very young and many things are yet to be identified, each business has some specific implementations of productive automation practices.

Hence, AI-ML engineering jobs may have many further responsibilities in IT organizations, like:

  • Coordination between data scientists and business analysts
  • Infrastructure Automation
  • Machine Learning models transformation into APIs
  • Test and deploy AI-ML models
  • Development of minimum viable products based on ML
  • Utilization of AI to empower businesses with new skills

How to become an AI-ML engineer?

Let's move on to the track, which is inescapable to pursue a professional career with the AI-ML engineering jobs. To start, keep in mind, you need to be formally educated with a bachelor’s or master’s degree in mathematics, statistics, computer science, data science, or any relevant subject to become an AI-ML engineer. Other than this, you also need command of the relevant technical and non-technical skills. Fresher AI-ML engineers may get jobs in start-ups and small businesses where they will work in multiple areas of AI-ML engineering.

However, you may have heard that to get remote AI-ML engineering jobs, you must have 3-5 years of experience. It is true for a couple of reasons.

  • First, industry experience allows you to recognize the vast opportunities while working remotely in top Silicon Valley companies.

  • Second, many organizations hire candidates with a proven track record to ensure a risk-free, fruitful hire.

Now, let's look at the skills and practices you'll need to understand to join the league of remote AI-ML engineers.

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Skills required to become an AI-ML engineer

The AI-ML engineering jobs sector is a relatively new and constantly evolving field. Because of this, there is no hard and fast skill set defined to become an AI-ML engineer. There are different scopes to get into the sector depending on your educational background, technical skills, and areas of interest. AI and ML are already reshaping industries like IT, FinTech, healthcare, education, transport, etc., and these have a long way to go. Organizations are shifting more to AI value, getting out of the experimentation phase, and focusing on expediting AI-ML adoption. Therefore, AI-ML engineering jobs will be more in demand in the near future.

If you want to push your career with an elite US job, the seven skills you need to master:

  1. 1. Programming languages

    The very first skill AI-ML engineers need to grow is their experience with multiple programming languages. According to GitHub, the top 10 machine learning languages include - Python, C++, JavaScript, Java, C#, Julia, Shell, R, TypeScript, and Scala. While Python is the most popular programming language, Scala is becoming popular in certain areas, like interacting with big data frameworks, such as Apache Spark.

  2. 2. Data engineering (ETL)

    For AI-ML system development, one crucial stage is pre-processing and storage of raw data that is generated by the systems. Every time when new data is generated, the AI-ML engineer needs to create ETL (Extract, Transform, Load) pipelines to process, cleanse and store data to make it easily accessible by other processes, such as analytics and predictions. AI-ML engineers need to recognize data models and connect the resolutions from data science with the fundamentals of software engineering.

  3. 3. Data analysis

    It is an essential skill for AI-Ml engineers to be able to conduct experimental data analysis on a dataset to recognize unusual patterns in data, define specific aberrations, and analyze hypotheses. To bag the best AI-ML engineering jobs, you should be able to create summary statistics for a dataset, generate graphical representations that allow for easy data visualization, clean and prepare data for modeling, perform feature engineering to obtain more information from the dataset, etc. to improve the ML models you will develop.

  4. 4. Models

    To become a pro in AI-ML engineering, you need to be exceptionally skilled in machine learning algorithms, as well as know when to implement those. Further, to do more complex tasks, like image classification, object detection, face recognition, machine translation, dialogue generation, etc., you need to have a good grasp of complex algorithms that are based on artificial neural networks.

  5. 5. Services

    Once you establish the most relevant machine learning model for solving a given problem, next you need to decide whether to implement the model from scratch or use existing services. If you need to develop new ML models and a fully managed platform that allows you to promptly and easily build, train and deploy those into a production-ready hosted environment, mastering in AWS SageMaker will be a great plus.

  6. 6. Security

    As in every software solution, managing security for AI-ML solutions is a crucial task. While the Machine Learning models need a lot of data preparation, data accessibility should be given to the authorized people and applications only. Data security is an exceptionally crucial skill to master.

  7. 7. Experience in real-life projects

    Another vital part of becoming an AI-ML engineer is recognizing where to apply your technical knowledge to actual tasks and assignments. Completing an AI-Ml engineering project end-to-end and documenting it in your portfolio will help you promote your skills and understanding to future employers.

  8. Interested in remote AI-ML engineering jobs?

    Become a Turing developer!

    Apply Now

How to get remote AI-ML engineering jobs?

AI-ML engineers need to work hard enough to stay updated with all the recent advancements in the AI-ML field and grow their skills gradually over time. In order to excel at their profession, they need to follow the best practices effectively and consistently. In this regard, there are two factors to consider for the engineers to focus on to progress. They might need to find support from someone who is more experienced and effective in training new techniques while they are practicing. Further, as an AI-ML engineer, it's vital to fine-tune the analysis, computer engineering, and artificial intelligence and machine learning skills. So, the engineers need to make sure there is someone who will help them out and keep an eye on their progress.

Turing offers the best remote AI-ML engineering jobs that suit your career trajectories as an AI-ML engineer. Grow rapidly by working on challenging technical and business problems on the latest technologies. Join a network of the world's best developers & get full-time, long-term remote AI-ML engineering jobs with better compensation and rapid career growth.

Why become an AI-ML engineer at Turing?

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Elite US jobs

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

Elite US jobs

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

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Career growth

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

Career growth

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

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Exclusive developer community

Join a worldwide community of elite software developers.

Exclusive developer community

Join a worldwide community of elite software developers.

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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.

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.

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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.

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.

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Great compensation

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

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 front-end developers?

At Turing, every front-end is allowed to set their rate. However, Turing will recommend a salary at which we know we can find a fruitful and long-term opportunity for you. Our recommendations are based on our assessment of market conditions and the demand that we see from our customers.

Frequently Asked Questions

What is Turing?
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.
How many rounds do I need to clear before selection?
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.
When working with Turing do I need to pay taxes in the U.S. or in my country?
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.
What kind of developers does Turing hire?
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.
What level English is necessary to get a job?
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.
Do you have positions for any other profile apart from developers?
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.
How is Turing different from other remote based job providers?
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.
Do developers need to pay any fees for Turing's services?
No, the service is absolutely free for software developers who sign up.
Does Turing hire fresh graduates?
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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Leadership

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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