Lead Applied Scientist - Computer Vision & Sensors (Remote)

SQUAD; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Gig-contract

21 paid vacation days per year

Medical insurance from day one

Remote work available within Ukraine

Job summary

SQUAD is seeking a Lead Applied Scientist to join our Research team. You will drive full-cycle research development in the sensors domain and report directly to the Head of Research. You will guide the team to meet key milestones and timelines, blending technical leadership with people management.

Your focus includes processing visual and low-level sensor data, along with coaching a team to deliver robust, scalable algorithms and features.

Qualifications

• 5+ years of research, data science, or data analysis experience.
• 1+ years of leading a research group or technical team on data science projects.
• Strong software engineering background with production-ready solutions.
• Deep theoretical and practical knowledge of Computer Vision algorithms.
• Solid understanding of deep learning frameworks, ML, and data analysis concepts.
• Proven Python proficiency.

Responsibilities

• Lead a team of 4-8 Applied Scientists to advance research projects and algorithmic performance.
• Own and maintain existing CV features.
• Prototype new features within computer vision and sensor domains.
• Coordinate with the data team to analyze research test data, develop evaluation metrics, and optimize algorithms.

Skills

Python

Computer Vision

Deep Learning

Data Analysis

Algorithms

Team Leadership

C++

English Communication

Education

Bachelor’s Degree in Math

Bachelor’s Degree in Computer Science

Bachelor’s Degree in Robotics or related field

Tools

AWS

Docker

Job description

SQUAD is seeking a Lead Applied Scientist to join our Research team. You will drive full-cycle research development in the sensors domain and report directly to the Head of Research. You will guide the team to meet key milestones and timelines, blending technical leadership with people management.

Your focus includes processing visual and low-level sensor data, along with coaching a team to deliver robust, scalable algorithms and features.