Computer Vision Engineer job description template

A computer vision engineer builds systems that extract usable information from images and video — detecting objects, measuring geometry, tracking motion, or classifying content. The role spans model development, the data pipeline that feeds it, and the engineering that gets it running reliably in production.

Before you post

Replace every bracket before posting — generic descriptions are the most common reason strong CV candidates skip a listing. Name the vertical and the actual problem early: candidates in this field self-select on problem domain more than on company brand. If C++ is genuinely optional, keep it under nice-to-have; listing it as required will halve your applicant pool.

The template

About the role

We are looking for a computer vision engineer to build and ship the perception capabilities behind [product]. You will own vision features end to end — from understanding the problem and shaping the dataset through to a model running reliably in production.

What you will do

  • Design, train and evaluate computer vision models for [specific task]
  • Build and maintain the data pipeline, including annotation workflows and quality checks
  • Take models to production and keep them working as the input distribution shifts
  • Define evaluation that reflects real product requirements, not just benchmark accuracy
  • Work with [product / hardware / platform] teams to turn requirements into a technical approach

What we are looking for

  • Practical experience building computer vision systems that reached real users
  • Strong Python and fluency with PyTorch or an equivalent framework
  • Solid grounding in image processing fundamentals alongside deep learning
  • Experience diagnosing model failures on real-world data

Keep this list to three to five items. Long mandatory lists disproportionately deter the candidates you most want.

Nice to have

  • C++ for performance-critical components
  • Experience in [your vertical]
  • Deployment experience on [your target platform]
  • Familiarity with annotation tooling and active learning

Plain text version

Select all and paste into your ATS, then replace everything in brackets.

COMPUTER VISION ENGINEER

ABOUT THE ROLE
We are looking for a computer vision engineer to build and ship the perception capabilities behind [product]. You will own vision features end to end — from understanding the problem and shaping the dataset through to a model running reliably in production.

WHAT YOU WILL DO
- Design, train and evaluate computer vision models for [specific task]
- Build and maintain the data pipeline, including annotation workflows and quality checks
- Take models to production and keep them working as the input distribution shifts
- Define evaluation that reflects real product requirements, not just benchmark accuracy
- Work with [product / hardware / platform] teams to turn requirements into a technical approach

WHAT WE ARE LOOKING FOR
- Practical experience building computer vision systems that reached real users
- Strong Python and fluency with PyTorch or an equivalent framework
- Solid grounding in image processing fundamentals alongside deep learning
- Experience diagnosing model failures on real-world data

NICE TO HAVE
- C++ for performance-critical components
- Experience in [your vertical]
- Deployment experience on [your target platform]
- Familiarity with annotation tooling and active learning

ABOUT US
[Two or three sentences on the company, the product, and why the problem matters.]

DETAILS
- Location: [city / hybrid / remote]
- Salary: [range]
- Apply: [link]

Calibrating the level

Adjust the requirements to match the level you are actually hiring for. Asking for senior capability at a mid-level budget is the most common cause of a stalled search.

Junior

Trains and fine-tunes models on well-specified problems, builds data tooling, works within an existing pipeline.

Mid

Owns a capability end to end — data, model, evaluation, deployment — and diagnoses failures without hand-holding.

Senior

Chooses the approach, decides when not to use deep learning, and is accountable for the system holding up on real data.

Staff / Principal

Sets technical direction across several vision systems and is the person who knows why the hard cases fail.

Post it where the right people are

JobsInVision is a computer vision job board — your listing reaches engineers who work in this field specifically, rather than a general software audience.