Information technology, software development, data jobs in Mlolongo, Kenya

32 jobs found

TELUS International

Robotics AI Specialist (AI Community)

Nairobi

Kenya

Closed for applications
World Vision

Head of ICT

Nairobi

Kenya

Closed for applications
Kenya Airways

Data Protection & Compliance Officer

Nairobi

Kenya

Closed for applications
Haco Industries Limited

Senior Applications Analyst

Nairobi

Kenya

Closed for applications
Absa Group Ltd

Specialist Platform Engineer

Nairobi

Kenya

Closed for applications
Environmental resource management

Managing Consultant - Ecologist (Mid-Senior Level)

Nairobi

Kenya

Closed for applications
MEDECINS SAN FRONTIERES

Application Manager - OpenMRS

Nairobi

Kenya

Closed for applications
Kipchimchim Group

Management Trainees- Information & Records Management

Nairobi

Kenya

Closed for applications
NCBA

System Administrator

Nairobi

Kenya

Closed for applications

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NCBA

Card Systems Analyst

Nairobi

Kenya

Closed for applications

Country / Region

Profession

Seniority (Information technology, software development, data)

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TELUS International

Computers + 1 more

Robotics AI Specialist (AI Community)

Closed for applications
Job details

Contract Type

Description

Mandatory Qualifications:

  • Education: Minimum of a Bachelor’s Degree in Robotics, Mechanical Engineering,or a related technical field.
  • Native Language: Native-level proficiency in your primary language is mandatory to assist in localized voice commands and regional safety documentation.
  • English Proficiency: Minimum B1 (Intermediate) level English for technical safety reporting and global collaboration.
  • Technical Interest: Basic understanding of computer vision, sensor fusion, or autonomous systems.


Responsibilities
  • Physical Data Evaluation: Audit video and sensor data to ensure robotic movements are logical, safe, and efficient.
  • Spatial Reasoning & Annotation: Provide expert feedback on 3D environments, helping AI models understand depth, distance, and physical obstacles.
  • Simulation & Digital Twin Testing: Review and grade AI performance in simulated environments to identify errors before hardware deployment.
  • Safety & Physics Validation: Ensure AI-generated physical instructions adhere to the laws of physics and rigorous engineering safety standards.
  • Edge-Case Detection: Identify complex real-world scenarios (e.g., lighting changes, surface textures, or moving hazards) that could confuse a robotic system.


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