ML Engineer Job Description: Qualifications and Responsibilities

How to Write a ML Engineer Job Description

The first step to hiring a great ML Engineer is being clear about what the role involves. An effective ML Engineer Job Description should explain what kind of work the candidate will be doing day to day, what skills are needed, and how this role fits into the bigger picture. When written well, it can help attract the right people and avoid confusion later on.

What is a ML Engineer / What does a ML Engineer do?

Machine Learning Engineers work at the intersection of data and engineering. They take models developed by data scientists and turn them into working systems that can scale. Whether it’s for recommendations, forecasting, or automation, ML Engineers help companies use data in practical, reliable ways.

The importance of a good ML Engineer Job Description

We’ve found that a good ML Engineer Job Description can save time in the hiring process. It helps candidates figure out if the role suits them and gives hiring managers a better pool of applicants to choose from. It’s also a chance to be clear about the tools, responsibilities, and expectations involved.

ML Engineer Job Description Template

About the role and the team:
We’re hiring an ML Engineer to help us build smarter systems using data. You’ll be working with product managers, engineers, and data scientists to bring machine learning models to life. This role is ideal for someone who’s curious, practical, and likes solving real-world problems with code.

Education & Training:

• Required education: A bachelor’s degree in Computer Science, Engineering, or something similar
  
• Preferred education: A graduate degree (Master’s or PhD) in Machine Learning, AI, or Data Science. Certifications in tools like TensorFlow or cloud platforms are helpful too
  

What your work might look like:

• Work with others to understand how ML can help with specific projects
  
• Train and test machine learning models, and make sure they’re ready to go live
  
• Build systems that keep models running and up to date
  
• Tweak models based on feedback or changes in the data
  
• Help spot problems early, like performance issues or data drift
  

Skills Requirement:

• Technical skills: Solid Python skills, experience with TensorFlow or PyTorch, and familiarity with AWS, GCP, or Azure
  
• Non-technical skills: Good communicator, collaborative mindset, and able to manage your own time
  
• Preferred (but not required) skills: Experience with tools like Kafka or Airflow, or working with real-time systems
  

ML Engineer Salary & Benefits

The average annual salary for ML Engineers in the U.S. is around $138,000, though many roles range from $110,000 to $160,000, depending on the company and location. Some of the benefits you might expect to see include:

• Health and dental coverage
  
• Mental health support or wellness stipends
  
• Learning budgets or access to industry conferences
  
• Equity or performance-based bonuses
  
• Hybrid or fully remote work options
  

Tailoring your ML Engineer Job Description

Common sub-types of ML Engineer roles

• NLP Engineers – Work on language models, chat tools, and text-based tasks
  
• Computer Vision Engineers – Focus on images and visual recognition projects
  
• MLOps Engineers – Build tools to manage, monitor, and scale ML systems
  

Adjusting for seniority

• Entry-level (0–2 years): Supportive learning environment, exposure to a range of tools
  
• Mid-level (2–5 years): More independent model building and ownership of small projects
  
• Senior-level (5+ years): Lead projects, mentor junior staff, and help guide ML strategy
  

Using Litespace for your resume screening

Litespace can help simplify the hiring process by giving you a smarter way to review resumes. Our AI Resume Screening Agent lets you create filters that match your ML Engineer Job Description. You’ll see a ranked list of strong candidates, and the system gives you full visibility into why they were selected. That means less guesswork and more time spent with the right people.