AI/ML/Data Engineers

Hire Data Engineers, AI/ML Experts

Data Engineering refers to a broad area of expertise that encompasses various topics. Its main focus is on creating reliable infrastructures, which enables the smooth flow of data in a world dominated by data. Data Engineers play a crucial role as connectors who link multiple sources of raw and refined data, making it easier for individuals within the organization to make informed data-driven decisions.

Artificial Intelligence (AI) and Machine Learning (ML) have brought about some of the most remarkable technological advancements seen in recent times. Their potential applications are limitless, with deployment possible in a variety of fields. AI provides assistance when the way forward is unclear, facilitating safe and precise parallel parking of vehicles, recommending new products or services based on user preferences, and even automating mundane chores like setting up meetings or selecting TV shows to watch.

With AI constantly evolving, we can expect more AI-powered voice assistants taking care of our daily routines within the next few decades.

There is an increasing demand for remote AI/ML/Data engineers, making this the perfect time to pursue a career in this field. To get started, it is crucial to gain an understanding of the role of an AI/ML/Data developer and the exclusive opportunities and challenges surrounding this profession.

What Prospects Await in AI/ML/Data Engineering?

The use of Artificial Intelligence (AI), Machine Learning (ML), and Data Engineering is gradually becoming more prevalent in today’s world. As a result, there is a growing demand for professionals with expertise in these areas. AI and ML have proven to be pivotal in enhancing specific human tasks like voice recognition, image processing, business process optimization, and disease detection. This means that these fields will continue to shape our collective future.

As AI, ML, and Data Engineering (DE) technologies become increasingly prevalent in various industries such as healthcare and education, the job market for professionals in these fields is growing exponentially. Data Engineering empowers businesses to take informed, data-driven decisions. The rising demand for these technologies presents numerous opportunities for developers seeking remote AI/ML/Data engineer positions.

What Tasks and Responsibilities Does an AI/ML/Data Engineer Have?

As an AI/ML/Data Engineer, you will be accountable for designing and testing algorithms and utilizing tools like R to generate models from the ground up, offering businesses with insights to make informed decisions. You will develop systems capable of being trained to forecast future trends, detect issues, and offer solutions. Once the models are created, it is your responsibility to deliver the final products to customers.

Here are the primary tasks of a developer after securing remote AI/ML/Data engineering employment.

• Transform machine learning models into Application Programming Interfaces (APIs) that can be utilized by other systems.
• Develop AI models from scratch and aid different areas of the organization in comprehending the output of the model.
• Arrange the setup of the data science team.
• Establish infrastructure for data input and transformation.
• Conduct statistical analysis and fine-tune the data to enhance the company’s decision-making.
• Establish and oversee infrastructure for developing and managing artificial intelligence products.

What are the steps to become an AI/ML/Data Engineer?

The right combination of skills and experience is crucial to begin or advance a career in AI/ML/Data Engineering. Most individuals who pursue this role possess a Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or a related IT field. It’s worth noting that a boot camp or certification may not be sufficient for this role as it requires a high level of technical knowledge.

Acquiring a degree provides a solid foundation of understanding in an industry that is always evolving. Pursuing a master’s degree can also help advance a career, qualifying one for well-paying remote job opportunities in artificial intelligence, machine learning, and data engineering.

Candidates for a remote AI/ML/Data Engineer position must have experience in SQL database design and programming skills in multiple languages such as Python and Java. Previous experience in IT, mathematics, analytics or related field can also be useful in building a strong resume. Moreover, candidates may enroll in a boot camp or accreditation program to further enhance their qualifications for the job.

If one does not have any prior experience with technology or information technology, enrolling in an intensive program may be necessary to demonstrate adequate understanding. For individuals without an undergraduate degree, a bachelor’s program is worth considering. Additionally, if an individual has a bachelor’s degree and is not working in a related field, acquiring a master’s degree in data analytics or data engineering can be a good option.

Browsing through job postings can help you gain a better understanding of how your skills align with the job requirements.

Requirements for becoming an AI/ML/Data Engineer

A crucial step towards a successful career as a remote AI/ML/Data Engineer is to first grasp the fundamental proficiencies for the role. To ensure one possesses the required skills for the job, let’s closely examine the essential abilities necessary for this type of work.

1. Python

   When working remotely in areas such as Artificial Intelligence (AI), Machine Learning (ML), and Data Engineering, the ability to process significant amounts of data accurately and quickly is crucial. Python is a widely-used language for these purposes thanks to its easy-to-understand syntax. Python’s syntax also makes it easy to link elements in complex systems explicitly. Another key advantage of using Python for AI development is the vast number of libraries available. These libraries provide essential objects that developers can use instead of having to create them from scratch each time. Given that AI applications require constant data processing, Python’s modules allow for efficient access, analysis, and updating of data.

2. Java

   Java is a programming language that is platform-independent and can operate on any machine. Thanks to Virtual Machine Technology, all platform-specific information can be included in a single package, allowing developers to swiftly create and deploy apps on any device. AI programming using Java encompasses numerous approaches such as machine learning, genetic algorithms, search algorithms, and neural networks.

3. C++

   C++ is a robust programming language that is exceedingly beneficial for AI/ML/Data developers. Its broad range of programming equipment and library functions make it well-suited to addressing difficult tasks. C++ follows object-oriented principles and is also a multi-paradigm language, hence it is excellent for organising data.

4. LISP

   LISP is a crucial programming language for those pursuing remote positions in Artificial Intelligence (AI), Machine Learning (ML) and Data Engineering. Despite being the second oldest programming language after Fortran, it has developed into a sophisticated and dynamic coding language. LISP’s adaptability and rapid prototyping and testing make it an excellent choice for AI applications, as it can swiftly and effectively solve specific problems.

5. Big data and Spark technologies

   Specialists in Artificial Intelligence (AI), Machine Learning (ML), and Data Engineering face the challenging task of managing and gaining insights into huge amounts of data regularly. This data can be likened to a digital library, and analysing it requires access to powerful big data technologies such as MongoDB and Cassandra. As AI software continues to evolve, increasingly intricate algorithms are needed for real-time analysis of data. These algorithms play a crucial role in providing insights into data and optimizing the development process.

6. Frameworks and Algorithms

   For anyone interested in pursuing a career in Artificial Intelligence (AI), Machine Learning (ML), or Data Engineering (DE), having a solid understanding of fundamental machine learning methods such as Linear Regression, K-Nearest Neighbours (KNN), Naive Bayes, Support Vector Machines (SVM), and other related techniques is essential. Additionally, when dealing with unstructured data such as images and videos, one must be well-versed in deep learning algorithms and their implementation using frameworks. To be qualified for remote AI/ML/DE employment, a strong grasp of key algorithms and frameworks is a prerequisite.

7. Hadoop

   The Apache Hadoop software library is a comprehensive framework that enables the distributed processing of large amounts of data across multiple interconnected devices. It is designed to scale up from a single server to tens of thousands of devices, each of which can provide processing and storage capabilities. This framework accommodates a variety of programming languages like Python, Scala, Java, and R, making it an incredibly versatile and powerful technology for handling massive volumes of data. However, Hadoop has some drawbacks such as delayed processing and a high learning curve due to the complex coding required.

How to secure work as a remote AI/ML/Data Engineer?

Each profession demands its own set of unique skills and traits. As a developer, it is critical to be aware of new opportunities to utilise your abilities. To execute work with utmost dedication and sincerity, one needs to have an eagerness to learn new things, embrace innovation, and view mistakes as learning opportunities.

At Works, we are committed to assisting AI/ML/Data engineers in achieving their career aspirations. We offer the best remote AI/ML/Data engineering positions available, providing access to cutting-edge technologies and the chance to tackle challenging technical issues. You can advance your career in 2022 with full-time, long-term remote AI/ML/Data engineering roles that provide excellent pay and opportunities for growth by joining our network of the most talented developers in the world.

Position Description

Job Responsibilities

• Develop AI/ML products with exceptional user experiences.
• Comprehend the project, develop a successful plan, and manage the entire project lifecycle.
• Devise and produce immensely scalable models/classifiers/algorithms employing ML/AI concepts.
• Collaborate with cross-functional teams to convey and impact the technical details of projects.
• Regularly integrate and deploy code into the cloud environment.
• In partnership with product managers, create wireframe mock-ups.
• Conduct usability sessions to refine processes, obtain buy-in, and advance towards complete deployment

Requirements

• Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
• Minimum of 3 years of experience in AI, ML, Deep Learning, or Natural Language Processing is mandatory (exceptions for highly skilled developers)
• Proficient in any general-purpose programming/query language, such as Python, SQL, PHP, Java, and C#.
• Fluency in English is necessary for collaborating with engineering management.
• Full-time employment opportunity (40 hours a week) with a 4-hour time zone overlap with the United States.

Desirable skills

• Familiarity with large systems, complex code bases, and version control systems like Git.
• Proficiency in ML libraries, predictive modelling, pattern recognition, data mining, among other areas.
• Understanding of popular data science toolkits like R, NumPy, MatLab, and others.
• Hands-on experience with machine learning frameworks and libraries (such as Keras and PyTorch) (like Scikit-learn, NLTK).
• Mastery over applied statistics, including regression, distributions, and statistical testing.
• Thorough understanding of Artificial Neural Networks and Deep Learning frameworks.
• Full-stack (FE & BE Development), Distributed & Parallel systems, and other related areas.
• Exceptional understanding of algorithms, data structures, and computer science principles.
• Perform and identify efficient solutions to problems without micromanagement.