Remote ML/data algorithm engineer jobs
We, at Turing, are looking for talented remote ML/data algorithm engineers who will be responsible for the design and integration of machine learning software to automate predictive models that offer real-time solutions. Here's the best chance to collaborate with top industry leaders while working with top Silicon Valley companies.
Find remote software jobs with hundreds of Turing clients
Job description
Job responsibilities
- Use exceptional mathematical skills to perform computations and work with the algorithms involved in programming
- Experiment innovative ideas for new systems and evaluate, maintain and upgrade old systems
- Solve complex problems with multi-layered data sets and optimize existing machine learning libraries and frameworks.
- Develop cost effective scalable ML systems and innovative algorithm solutions
- Manage design, development and deployment of scalable, high volume and real time system
- Clean documentation of the machine learning processes
Minimum requirements
- Bachelor’s/Master’s degree in Computer Science, Electric Engineering, Physics, Statistics, Applied Mathematics (or equivalent experience)
- 3+ years of experience ML engineering (rare exceptions for highly skilled developers)
- Solid understanding of machine learning evaluation metrics and best practices
- Detailed knowledge of data structures and algorithms
- Extensive knowledge of ML frameworks and libraries
- Experience in developing and debugging multithreaded and/or parallel applications
- Familiar with UNIX environment and Linux SysAdmins
- Proficiency in programming languages such as Python, R, etc.
- Significant knowledge of messaging libraries including, Kafka, RabbitMQ, ZeroMQ, etc.
- Strong competence with infrastructure as code like Terraform, Cloudformation, etc.
- Experience in developing and deploying machine learning services
- Fluent in English to communicate effectively
- Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones
Preferred skills
- Understanding of MLOPs technologies and workflow
- Ability to work with large, complex datasets
- Ability to articulate at a system level
- Knowledgeable of explaining complex process to non-technical audience
- Keen attention to detail
- Knowledge of cloud computing environments
- Great technical, analytical and problem-solving skills
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How to become ML/Data Algorithm engineer ?
ML/Data Algorithm engineers, sometimes known as algorithm developers, are in charge of designing and integrating algorithms. In a software or computer environment, these well-designed algorithms provide real-time solutions when implemented. ML/Data Algorithm engineers create algorithms that are valuable in a range of industries, such as web engineering and signal processing.
ML/Data Algorithm engineers are typically regarded as highly skilled programmers due to commonalities in shared coding languages. They create algorithms to assist clients or employers in solving problems or achieving desired outcomes.
A career as an ML/Data algorithm engineer, among other reputable information technology careers to pursue, is suitable for persons with a flair for specific technology, coding languages, and data sets, as well as a passion for problem-solving.
What is the scope of ML/Data algorithm engineering?
ML/Data algorithm engineering is already having an impact on our future, and there is a growing demand for experienced engineers. AI and machine learning appear to hold the key to improving specialized human tasks including speech recognition, image processing, business process management, and even illness diagnosis.
Since these technologies are being employed in a variety of industries around the world, including healthcare and education, career opportunities have increased at an exponential rate. Similarly, data engineering is a field that assists businesses in making data-driven decisions. The increasing popularity and uses of these technologies offer a bright future for developers working for remote ML/Data algorithm engineer employment.
What are the roles and responsibilities of an ML/Data algorithm engineer?
An algorithm engineer will be responsible for a variety of tasks, the majority of which are related to the development of algorithms for use in AI systems. An algorithm engineer's specific work responsibilities may include:
- The development of algorithms for AI applications that recognize patterns in data and make conclusions from them.
- Algorithm testing for AI technology, software programs, and machine-learning applications.
- Organize the configuration of the data science team.
- Create infrastructure for data input and transformation.
- Perform statistical analysis and fine-tune the results so that the company can make better decisions.
- Algorithm reporting is used to identify and display findings in easy-to-read report formats.
- Investigate potential algorithm improvements to improve algorithm efficiency.
- Communication with teammates, algorithm engineers, and clients.
How to become ML/Data algorithm engineer?
You'll need a few requirements to work as an ML Engineer. This role is in charge of developing high-performing machine learning systems by evaluating and organizing data, running tests and experiments, and generally monitoring and optimizing the learning process.
As an ML Engineer, you'll be in charge of applying algorithms to a variety of codebases, therefore previous software development experience is a plus. The correct combination of math, statistics, and web programming will give you the requisite background – once you grasp these concepts, you'll be ready to apply for ML Engineering jobs.
Interested in remote ML/Data Algorithm engineer jobs?
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Skills required for ML/Data algorithm engineer
ML/Data Algorithm engineers utilize their highly developed skills to assist clients in improving processes and locating solutions in data sets regularly. The most important skills that every company look for in remote ML/Data algorithm engineers are:
1. Algorithm design and implementation
Ability to construct and implement algorithms to solve client problems and contribute to AI capabilities (algorithm creation and deployment skills).
2. Data science
Familiarity with programming languages such as Python, SQL, and Java; hypothesis testing; data modeling; competency in mathematics, probability, etc. and the ability to build an assessment approach for predictive models and algorithms are just a few of the data science principles that machine learning engineers rely on.
3. Statistics
Learn Naive Bayes classifiers, Bayes rule, and Bayes nets, conditional probability, likelihood, Hidden Markov Models, and so on
4. ML Aptitude
The ability to integrate algorithms and statistical models with computer systems that find data patterns is referred to as machine learning aptitude.
5. Advanced coding skills
The ability to write algorithms to analyze data sets using programming languages such as Python and C++.
6. Analytical thinking
The capacity to evaluate a project critically and create an algorithm that searches through data sets to reach certain conclusions.
7. Signal processing
Skills in signal processing include the capacity to analyze and synthesize signals to improve transmission, storage, and data quality.
8. Derivative analysis
The ability to offer real-time algorithm findings to company management is one of the most important abilities to have.
9. Leadership skills
Ability to work with other algorithm engineers and team members to meet project deadlines.
Interested in remote ML/Data Algorithm engineer jobs?
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How to get remote ML/Data Algorithm engineer jobs?
ML/Data Algorithm engineers must work hard enough to keep up with all of the industry's current breakthroughs and to steadily expand their expertise. To be effective and consistent in their sector, they must adhere to the best practices. In this sense, developers should keep two things in mind as they move forward. While practicing, they may seek assistance from someone more experienced and adept at teaching new skills. In addition, as a machine learning engineer, you must sharpen your analytical, computer programming, artificial intelligence, and machine learning skills. As a result, the developers must ensure that someone is available to assist them.
Turing provides the greatest ML/Data Algorithm engineers jobs that can help you achieve your ML/Data Algorithm engineering career objectives. Working with cutting-edge technologies to solve complex technical and business problems will help you expand quickly. Join a network of the world's best developers to get full-time, long-term remote ML/Data Algorithm engineers employment with higher salaries and faster career advancement.
Why become ML/Data Algorithm engineer at Turing?
Elite US jobs
Long-term opportunities to work for amazing, mission-driven US companies with great compensation.
Career growth
Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.
Exclusive developer community
Join a worldwide community of elite software developers.
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
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
Working with top US corporations, Turing developers make more than the standard market pay in most nations.
How much does Turing pay ML/Data Algorithm engineers?
Every ML/Data Algorithm engineer at Turing can set his or her rate. Turing, on the other hand, will recommend a salary at which we are confident of providing you with a satisfying and long-term opportunity. Our recommendations for remote ML/Data Algorithm engineer jobs are based on industry research and demand from our most famous clients.
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