Machine Learning Engineer

Overview

Data Scientist/Machine Learning at
Crescer AI
Post Date: April 2025

Snapshot
Role: Machine Learning Engineer
Employee type: Full-time
Location: Remote
Start date: ASAP
Compensation: Competitive salary, equity

Who is Crescer AI?
Crescer AI is an advanced technology consultancy geared towards helping enterprises solve intractable problems using AI. Our team has worked with high impact companies including the likes of NASA, Amazon, Deloitte, and Ford where we developed a unique set of expertise in applied artificial intelligence, deep learning, and product development.

Description
In this role you will:

• Work on a variety of machine learning challenges with practical applications in the GIS and aerial mapping space
• Drive R&D machine learning initiatives to improve product performance and user experience
• Robustify and deploy your work into production environments
• Maintain readable and unit testable code with documentation

What we need from you:

• 1 - 3 years experience as a data scientist, computer vision engineer, or machine learning engineer
• Worked with point clouds or images and two or more of the following concepts: statistical (classical) methods for computer vision or machine learning, modern machine learning (neural networks), data engineering
• Strong data visualization and communication skills
• Available to work full-time
• Comfortable collaborating with international teams (USA)
• Comfortable developing in Linux

Bonus points for:
∙ Familiarity with scrum, kanban, agile practices
∙ Familiarity with MLOps

Application Instructions
Join us and play a critical role in the development of AI solutions and products for enterprise.
Please use the indeed platform to proceed with the application. We appreciate your interest and look forward to your application.

Website: www.crescer.ai

Job Type: Full-time

Pay: ₹1,200,000.00 - ₹2,400,000.00 per year

Application Question(s):

• Describe a specific ML or CV architecture you've implemented in real projects? Explain why you chose that architecture, what problem it solved, and any adaptations you made to fit your specific use case. Please be concise but complete in your response.
• Describe a challenging ML/CV project you worked on. What was difficult about it and how did you overcome those challenges? Please be concise but complete in your response. Bonus for using a different example than the above question.

Experience:

• Data Science, Computer Vision, or Machine Learning: 1 year (Required)

Work Location: Remote