What Does A Machine Learning Engineer Do? Building Better AI (2023 Guide)

Better data means better opportunities to explore and make decisions. The accessibility of data with the required shape and volume enables data scientists and data analysts to generate data visualizations for non-technical end-users.

Besides, the Artificial Intelligence and Machine Learning revolution has reformed the way businesses were operating and making decisions. In all of this, hiring a talented workforce that really implements the way you imagine and achieves success earlier in Artificial Intelligence.

Although it’s sometimes hard to get profitable results in artificial intelligence and machine learning. Nevertheless, hiring a talented machine learning engineer with staff augmentation services may cater to your dream earlier than your expectations.

What is a machine learning engineer?

A machine learning engineer is a highly skilled professional who specializes in designing, developing & implementing complex algorithms and models that enable machines to build intuition with data.

ML engineers or machine learning engineers possess a unique blend of skills in computer science, statistics & mathematics. These problem-solving skills allow them to build sophisticated AI systems that can solve complex problems & provide valuable insights from reservoirs of data.

Machine learning engineers work on cutting-edge technology projects, from creating time series forecasting systems and natural language-based knowledge graphs to developing predictive models and computer vision solutions.

They are responsible for identifying the most suitable ML techniques, cross-validating, testing & fine-tuning models, and deploying solutions at production. Now, are you excited to learn the day-to-day responsibilities a machine learning engineer fulfills with some skillset? Let us help you in this matter.

Responsibilities of Machine Learning Engineers & Required Skills

Machine learning engineers are just part of the data transformation from data acquisition to data visualization. They have fixed responsibilities to available machine learning models to data scientists. The data scientists then use these ML models to draw fruitful insights for stakeholders and available analyzed data to data visualization engineers.

A potential ML engineer should have the following skills to get rewarded as the best AI talent behind digital transformation. Here’s a list of the required skill sets a software engineer should have to become a successful machine learning engineer.

  • Expert in Programming

    Machine learning engineers are proficient in at least one programming language from Python, R, or Java. The ML engineers should be able to write clean, robust & scalable software modules.

  • Knowledge of Data Structures & Algorithms

    Machine learning engineers have a strong understanding of data structures and algorithms, including graph algorithms, dynamic programming & sorting algorithms.

  • Adept in ML Algorithms

    Machine learning engineers have a deep knowledge of various traditional and modern machine learning algorithms like linear regression, logistic regression, decision trees, neural networks, and clustering algorithms.

  • Strong Mathematical & Statistical Skills

    ML engineers also have a strong foundation in mathematical as well as statistical concepts like linear algebra, calculus, probability & statistics.

  • Knowledge of Data Management & Processing Tools

    Machine learning engineers also have proficiency in tools like SQL, Hadoop, Spark & NoSQL databases for data management as well as processing.

  • Good Communication Skills

    Machine learning engineers work closely with high-level executives so they have effective communication skills with team members, stakeholders, and clients.

Similar Roles to Machine Learning Engineers

In addition to the above, machine learning is not an explicit role in some organizations because sometimes, data scientists are fulfilling the role of machine learning engineers or sometimes data analysts but these roles are different with different skill sets and problem-solving. Let’s shed some light on each role.

Deep Learning Engineers

The deep learning engineers are only responsible for training, testing & building modern deep learning models. In short, they available best-performing high dimensional models to data scientists & data analysts.

Data Scientists

Data scientists use statistical and machine learning techniques to revamp data by using different data pre-processing and transformation strategies to make data understandable for laymen.

Data Analysts

Data analysts collect, process & perform statistical analyses on large datasets to help organizations make data-driven decisions.

Artificial Intelligence Engineers

Artificial intelligence engineers innovate new strategies and algorithms for available AI for social good. They mostly do research and development but are experts in machine learning, deep learning, and even process automation.

ML Consultants

In addition to the above, ML consultants are professionals who provide expertise & guidance in implementing machine learning solutions for businesses. They usually help companies leverage data to improve decision-making & optimize business processes.

Machine Learning Engineer Salaries 2023

ML engineer salaries depend upon multiple factors including location, skillset, exposure to industries & ability to tackle real-world problems. Here we have some salary stats from famous job portals i.e. Glassdoor and Indeed.

Glassdoor: ML Engineer Salary Quotes

According to Glassdoor, as of April 2023, the average base salary for an ML engineer in the United States is around $130k/year. However, this can vary significantly depending on the location or skill set. For example, machine learning engineers in San Francisco, New York City & Seattle tend to earn higher salaries compared to other cities.

Indeed: Machine Learning Engineer Salary Bracket

Indeed is another popular job search platform that provides salary estimates for machine learning engineers. As of March 2023, the average annual base salary for an ML engineer in the United States is approximately $130k.

Hire Machine Learning Engineers Today: Odyssey Analytics

Hiring an affordable, talented & true problem-solver machine learning engineer is hard today. Odyssey Analytics is a staff augmentation services provider in the United States. We offer multiple talents as a service including data scientists, data engineers, cloud migrations experts, and software quality assurance engineers. We provide dedicated resources and teams. Are you excited to onboard ML resources? Hire machine learning engineers now.

Frequently Asked Questions

What are the essential tasks of a machine learning engineer?

The essential tasks of a machine learning engineer include developing and implementing machine learning models, collecting and analyzing data, and integrating machine learning algorithms into software applications.

How to hire machine learning engineers?

To hire machine learning engineers, companies should look for candidates with relevant education and experience, strong technical skills, and the ability to work collaboratively in a team environment.

Can ML experts help in computer vision projects?

Yes, ML experts can provide valuable insights and expertise in computer vision projects, as many computer vision applications rely on machine learning algorithms for object recognition and image analysis.

Why should you hire remote ML engineers?

Hiring remote ML engineers can provide access to a wider pool of AI talent, reduce overhead hiring costs, and increase team flexibility and agility.

Do machine learning engineers do coding?

Yes, machine learning engineers typically spend a significant amount of time coding, as they are responsible for designing, developing, and implementing machine learning algorithms and models.

What is required for a machine learning engineer?

To become a machine learning engineer, individuals typically need a strong background in mathematics, computer science, and statistics, as well as experience with programming languages and machine learning frameworks.

What skills should a machine learning engineer have?

The essential skills for machine learning engineers include familiarity with a programming language, data analysis, statistical modeling, and problem-solving. Besides, It is mandatory to have strong communication and collaboration skills.