Senior AI/ML Engineers

Hire Senior AI/ML Engineers

Our future is already being shaped by artificial intelligence (AI) and machine learning. As they grow in popularity, so does the need for competent developers. AI and machine learning are two terms that are being used interchangeably right now. They are not the same, although the similarity might cause misunderstanding. Remote senior AI/ML engineer positions are on the rise as more businesses across the globe adopt automation. You can become a top AI/ML developer if you have enough experience and have fine-tuned your AI/ML skill set. AI/ML development is a reliable and well-paying remote career option.

Researchers, planners, and producers of self-running Artificial Intelligence systems to automate predictive models are the primary focus of AI/ML developers. Remote AI/ML engineer jobs also entail creating and building AI algorithms that can learn and provide predictions that explain Machine Learning. It enables engineers to learn from the data fed into machine learning algorithms rather of depending on a set of procedures.

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

What does senior AI/ML development entail?

Because AI/ML engineer positions are in great demand across sectors, they provide employment stability and a plethora of prospects. The worldwide demand for AI/ML technology and applications has resulted in a rise in the number of AI startups and greater interest in the topic among established businesses. Since 2010, the number of AI startup acquisitions has more than quadrupled, almost quadrupling between 2015 and 2018.

According to one report, the rise in AI company acquisitions has been paralleled by the rise in AI startup funding, which has risen from more than a billion dollars in 2013 to 8.5 billion dollars in the first quarter of 2020. Remote AI/ML developer job advertisements are seldom empty since highly qualified AI/ML developers are in great demand across sectors.

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.

  • Create a Machine Learning method to transform the UX team’s whiteboard drawings of website layouts into final layouts for the Software development team.
  • Use the strategy to help organizations 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.
  • Create a model that connects HotJar and A/B testing results with Google Analytics data and statistics. It will help with the creation of better layouts, which will result in greater time spent on the site, higher customer acquisition, and so on.
  • 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 high degree of expertise and experience necessary for these programming jobs, anybody with a genuine interest in the field—and the capacity to perform at least some of the previous tasks of a senior AI/ML developer—can get remote senior AI/ML engineer positions.

There are many paths you may take to become a senior AI/ML developer. The most common way to get started is to enroll in college. When it comes to joining the profession, a computer science degree will provide you with a firm foundation and credentials. College is costly, and the length of time it takes to finish it is a drawback. Furthermore, if you don’t have good grades in high school, you may not be able to enroll in a college that will help you get senior AI/ML engineer employment.

Another alternative is to enroll in a boot camp program. The emphasis will be on teaching you the languages you’ll need to apply in person or online for remote senior AI/ML engineer positions. This may be a less costly and speedier option than a three- or four-year degree, depending on the boot camp.

Whatever route you choose to become a remote senior AI/ML engineer, you can be certain that you will have a bright future and lots of career prospects.

Qualifications for a senior AI/ML engineer

Learning the requisite abilities is the first step toward getting high-paying senior AI/ML engineer employment. Let’s look more closely at each of the technical talents.

  1. Computer programming languages

    Working with numerous programming languages is a necessary skill for remote senior AI/ML engineer employment. The top ten machine learning languages, according to GitHub, are Python, C++, JavaScript, Java, C#, Julia, Shell, R, TypeScript, and Scala.
  2. Data collection

    One of the most significant phases in the development of AI/ML systems is the pre-processing and archiving of raw data produced by these systems. When new data is created, the AI/ML developer must design ETL pipelines to process, cleanse, and store it so that it can be accessible by other processes such as analytics and predictions. For AI/ML developers, data scientists must be able to detect data models and relate data science resolutions to software development concepts.
  3. Data examination

    To perform better in interviews for remote senior AI/ML engineer positions, you must be able to execute experimental data analysis on a dataset to uncover unusual patterns in data, define particular aberrations, and test hypotheses. You should be able to construct summary statistics for a dataset, build graphical representations that allow for simple data visualization, clean and prepare data for modeling, and design features to extract additional information from the dataset. So on, in order to enhance the ML models you create.
  4. Models

    To thrive in AI/ML development, you must be an expert in machine learning methods and their best applications. Furthermore, in order to do increasingly difficult tasks such as picture classification, object identification, facial recognition, machine translation, dialogue synthesis, and so on, you’ll need a thorough grasp of sophisticated algorithms based on artificial neural networks. So, in order to get hired for the greatest remote senior AI/ML engineer jobs, you must master this talent.
  5. Security

    As with any other software solution, security is critical for AI/ML systems. While extensive data preparation is necessary for Machine Learning models, data access should be restricted to authorized employees and applications only. Data security is a skill that must be learnt at all costs before applying for remote senior AI/ML engineer employment.
  6. Real-world project experience

    Another important component of being an AI/ML developer is knowing when and how to apply your technical knowledge to real-world activities and projects. Completing an AI/ML development project from start to finish and documenting it in your portfolio can assist you in pitching your talents and expertise to prospective employers, helping you to obtain those remote senior AI/ML engineer positions you’ve always wanted.

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

We’ve seen the requirements for remote senior AI/ML engineer positions. The most essential thing is to always offer your best effort while practicing. Every day, new technology developments alter industries. More individuals will join the field as it grows more popular, increasing your competition. Keeping up with current industry trends can help you advance your career.

Works features the greatest remote senior AI/ML engineer jobs to assist you in reaching your AI/ML engineer goals. You’ll also get the chance to hone your talents by working on difficult technical issues with other talented engineers. Join a worldwide network of top senior AI/ML engineers to discover full-time, long-term remote senior AI/ML engineer employment with greater pay and opportunities for promotion.

Job Description

Responsibilities at work

  • Advanced machine learning, deep learning, and NLP/NLU approaches should be used.
  • Collaborate with AI researchers, AI engineers, and product managers to brainstorm software ideas, conduct trials, and develop new market-fit products.
  • 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 modeling.
  • Expertise in managing production utilizing deep learning frameworks such as TensorFlow and PyTorch, as well as workflow technologies such as 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.