Machine Learning Engineer

Machine Learning Engineer (Computer Vision)

Location:

Experience:

About Perleybrook Labs:

AI-driven safety, automation, and quality-intelligence systems

unify vision, intelligence, and action

real production systems

learn deeply by doing

This role is for you if:

• You want to learn how

  production-grade computer vision systems

  are built
• You enjoy

  hands-on problem solving, experimentation, and iteration

• You’re excited to work in a

  fast-moving startup with real customers

• You care more about

  growth, exposure, and impact

  than short-term pay
• You will work closely with founders, engineers, and field teams—and gain 

  end-to-end exposure

   from data to deployment.

What You Will Work On:

• Building and improving

  computer vision models

  for real industrial environments
• Curating, cleaning, and managing

  high-quality datasets

• Training and optimizing

  object detection models

  (YOLO-based architectures)
• Working closely with

  annotation teams

  to ensure data consistency and accuracy
• Evaluating feasibility of new

  vision use cases and AI-driven features

• Analyzing model performance, failures, and edge cases and fixing them
• Learning how models move from

  training → optimization → deployment

hands-on engineering role

What We are Looking For:

• 1–2 years of experience (or strong projects) in

  Computer Vision / Machine Learning

• Practical experience with

  PyTorch

• Familiarity with

  YOLO or similar object detection models

• Understanding of training concepts such as:

Learning rate, Batch size, Data augmentation, Overfitting, Hyperparameter tuning

• Experience working with

  datasets, annotations, and validation workflows

• Ability to communicate clearly with

  engineers, annotators, and product teams

• Strong curiosity and willingness to

  learn fast and work close to the product

Nice to Have (You Will Learn This Here If You Don't Know Yet):

• Model optimization techniques (quantization, pruning)
• ONNX export and inference pipelines
• Exposure to

  edge deployment

  or real-time inference constraints
• Experience with

  production ML challenges

  (data drift, edge cases, latency)

What You Will Gain (Why This Role is Valuable):

• Work on

  real-world AI systems

  , not toy problems
• Learn how

  industrial vision products

  are designed, trained, and deployed
• Exposure to

  international customers and use cases

• Direct mentorship and feedback in a

  high-performance startup environment

• Opportunity to grow into

  senior engineering or architecture roles

• A strong learning curve that significantly increases your

  long-term career value

early career as an investment phase

Compensation & Expectations (Transparent):

• We optimize for

  learning, ownership, and exposure

  , not inflated titles or pay
• Growth opportunities scale as the

  company and product scale

How to Apply:

product, mission, and learning opportunity

Apply with:

• Your resume
• GitHub / project links (if available)
• A short note on

  why Perleybrook Labs interests you