Senior AI/ML Engineers

Hire Senior AI/ML Engineers

As Artificial Intelligence (AI) and Machine Learning (ML) continue to evolve and become increasingly popular, the demand for highly skilled developers to work on these technologies grows. Although there may be some confusion between the two terms as they are often used interchangeably, it is important to note that AI and ML are distinct from one another. Remote senior AI/ML engineer roles are becoming increasingly common as more companies around the world embrace automation. Those with the necessary experience and expertise in AI/ML can become successful developers in this field and can reap the rewards of a well-paid and stable remote career.

AI/ML developers are primarily focused on researching, planning, and producing self-running Artificial Intelligence systems that automate predictive models. Remote AI/ML engineer jobs also involve creating and constructing AI algorithms that can learn and provide predictions based on Machine Learning. This capability allows engineers to gain insights from the data fed into machine learning algorithms, instead of relying on a predefined set of processes.

Let’s look at some additional facts regarding remote senior AI/ML engineer jobs before you apply.

What does senior AI/ML development entail?

Due to the ever-increasing demand for AI/ML engineers across all industries, these positions offer a high degree of job security and numerous opportunities for growth. The global demand for AI/ML technology and applications has resulted in an influx of AI startups, as well as a heightened interest in the field from more established companies. This is reflected in the dramatic rise in the number of AI startup acquisitions, which have more than quadrupled since 2010 and almost quadrupled between 2015 and 2018.

According to a recent report, the growth in Artificial Intelligence (AI) company acquisitions has been mirrored by the exponential increase in AI startup funding, which has grown from over one billion dollars in 2013 to an impressive 8.5 billion dollars in the first quarter of 2020. This surge in investment has also been reflected in the job market, with highly qualified AI/Machine Learning (ML) developers in high demand across all sectors. As a result, job postings for remote AI/ML developers are rarely unfilled.

What are the duties and obligations of a senior AI/ML engineer?

The following are some of the most critical tasks after securing remote senior AI/ML engineer employment.

• The UX team is creating whiteboard drawings of website layouts, and the Software development team needs these drawings to be transformed into final layouts. To facilitate this process, we should develop a Machine Learning method which will enable us to quickly and efficiently convert the whiteboard drawings into the final layouts that the Software development team requires.
• Use the strategy to help organisations save time and money by speeding up feedback loops for website UX modifications.
• Using data from several HotJar users and machine learning techniques, identify common threats and sources of user distraction.
• We should develop a model that integrates HotJar and A/B testing results with Google Analytics data and statistics. This integration will provide the necessary information to create more effective web page layouts, resulting in increased user engagement and thus higher customer acquisition. Additionally, we anticipate that this integration will also lead to increased time spent on the site which would have a positive impact on overall customer experience.
• Evaluate the effectiveness of different layouts recommended by the UX team.

How do you get to the position of senior AI/ML engineer?

Despite the fact that a high level of expertise and experience is required to work in the field of Artificial Intelligence and Machine Learning, anyone with a true passion for the subject and the capacity to carry out some of the duties of a Senior AI/ML Developer can attain a remote Senior AI/ML Engineer position.

If you are interested in pursuing a career in AI/ML engineering, there are several pathways you can take. Attaining a college degree is one of the most common routes for those looking to enter the field. While a degree in computer science can provide individuals with the background knowledge and credentials necessary for the profession, it can be costly and time consuming. Furthermore, those without strong high school grades may not be eligible for enrollment in colleges that may provide the necessary prerequisites for senior AI/ML engineer employment.

Enrolling in a boot camp program is a viable alternative to pursuing a three or four year degree. Boot camps emphasise teaching students the languages necessary to apply for senior AI/ML engineering positions, both in-person and remotely. Depending on the specific boot camp, this option may be more cost-effective and quicker than a traditional degree program.

Whichever path you decide to pursue in order to become a remote senior Artificial Intelligence/Machine Learning engineer, you can be certain that you will have an abundance of opportunities for advancement and a very promising future.

Qualifications for a senior AI/ML engineer

Gaining the necessary skills and knowledge is the initial step towards securing a rewarding position as a senior AI/ML engineer. In order to better understand what these technical abilities involve, let us take a closer look at each of them.

1. Computer programming languages

   As a remote Senior AI/ML Engineer, it is important to develop proficiency in a variety of programming languages. According to GitHub, the top ten machine learning languages are Python, C++, JavaScript, Java, C#, Julia, Shell, R, TypeScript, and Scala. Acquiring a comprehensive understanding of these languages is essential when applying for remote Senior AI/ML Engineer roles.

2. Data collection

   One of the most important steps in designing Artificial Intelligence and Machine Learning systems is pre-processing and archiving of the raw data they generate. As new data is created, developers must construct Extract, Transform, and Load (ETL) pipelines to process, cleanse, and store the information so that it can be readily used in other processes such as analytics and predictions. AI/ML developers and data scientists must also be able to recognise data models and relate data science solutions to software development principles.

3. Data examination

   In order to be successful in interviews for remote senior AI/ML engineer positions, it is essential to demonstrate expertise in data analysis. This includes being able to execute experimental data analysis on a dataset in order to uncover any unusual patterns or aberrations, as well as being able to test hypotheses. Additionally, it is important to be able to construct summary statistics, create graphical representations that allow for simple data visualisation, clean and prepare data, and design features to extract additional information from the dataset, all in order to improve the ML models that are created.

4. Models

   In order to be successful as an AI/ML developer, it is essential to have an in-depth understanding of machine learning methods and their most effective applications. This knowledge must be supplemented with expertise in advanced algorithms, based on artificial neural networks, to perform difficult tasks such as picture classification, object identification, facial recognition, machine translation, and dialogue synthesis. To secure the best positions in remote senior AI/ML engineering, it is critical to have a mastery of these skills.

5. Security

   Security is a foundational element to any software solution, particularly those involving Artificial Intelligence (AI) and Machine Learning (ML). Before seeking remote senior AI/ML engineer employment, it is essential to understand the importance of data security and how to properly implement it. Data preparation is a necessary step for ML models, but access to the data should be strictly limited to the appropriate personnel and applications. Ensuring the security of the data is a skill that must be mastered to ensure the success of any AI/ML system.

6. Real-world project experience

   Having a thorough knowledge of AI/ML is essential for any aspiring AI/ML developer. However, applying this knowledge to real-world projects and activities is equally essential. Creating a portfolio which showcases a completed AI/ML development project from start to finish can be a powerful tool in convincing potential employers of your skills and capabilities. Such a portfolio can help to open doors for the remote senior AI/ML engineer positions that you strive for.

Where can I find remote senior AI/ML engineer jobs?

In the current job market, the demand for remote senior AI/ML engineers is growing exponentially. As the industry continues to evolve with the emergence of new technologies and more people joining the field, it is essential to stay up-to-date with the latest trends to keep your competitive edge. To succeed in this highly competitive field, it is important to always strive to do your best work and remain diligent in your effort. By keeping abreast of the changes in the industry, you can stay ahead of the curve and continue to progress in your career.

At Works, we provide you with the best remote senior AI/ML engineer jobs to help you achieve your career ambitions. We give you the opportunity to refine your skills and take on challenging technical tasks together with experienced engineers from all around the world. With our platform, you can find excellent full-time, long-term remote senior AI/ML engineer positions that offer competitive salaries and potential for career advancement. Join our global network of accomplished senior AI/ML engineers and take the next step in your career!

Job Description

Responsibilities at work

• Advanced machine learning, deep learning, and NLP/NLU approaches should be used.
• By working together with Artificial Intelligence researchers, Artificial Intelligence engineers, and product managers, we can explore potential software concepts, carry out experiments, and create new products that meet customer demand. Through this collaborative effort, we can ensure that our products are developed to the highest standard, giving us the best chance of success in the marketplace.
• Contribute to the containerization, orchestration, and DevOps deployment of cutting-edge AI systems for faster delivery and better maintenance.
• To create and deliver software solutions, use corporate SDLC and enable CI/CD deployment of microservices.
• Demonstrate the final goods’ usefulness, applicability, and performance.
• Remove superfluous complications and make complicated AI/ML issues understandable and accessible to company managers.
• Pipelines for data augmentation must be defined, developed, and maintained.
• Work with cross-functional teams to generate goals, concepts, and deliverables, as well as mentor younger developers/engineers.

Requirements

• Bachelor’s or Master’s degree in Engineering, Computer Science, Applied Statistics, or Mathematics is required (or equivalent experience)
• At least 5 years of experience as an AI/ML engineer is required (rare exceptions for highly skilled engineers)
• Solid understanding of machine learning, AI, and software engineering fundamentals.
• Excellent knowledge of machine learning methods for regression, classification, clustering, and data modelling.
• I possess a high level of proficiency in operating production systems that utilise deep learning frameworks, like TensorFlow and PyTorch, as well as workflow technologies, including Kubeflow.
• Keep up with the newest AI/ML technology developments.
• Knowledge of one or more programming languages, such as Python and R.
• Strong command of the English language is required for efficient communication.
• Work full-time (40 hours a week) with a 4-hour overlap with US time zones.

Preferred skills

• Advanced software tools, libraries, and languages, as well as image recognition and GPU, are required.
• Capability to measure, comprehend, and troubleshoot interconnected systems.
• Extensive knowledge of Frequentist and Bayesian statistics.
• Working knowledge of Git and DevOps technologies.
• Understanding of the Spark and Databricks platforms.
• Knowledge of cloud services such as Azure, AWS, or GCP.
• Worked extensively in an Agile/Scrum context.
• Outstanding time management and leadership abilities.
• Excellent interpersonal and communication abilities.