Junior AI Engineer - Computer Vision

About InnovationTeam: InnovationTeam is a premier, internationally recognized technology pioneer, artificial intelligence innovator, and data-driven solutions leader on an absolute mission to deliver advanced machine learning systems across multiple enterprise industries. By specializing in migrating complex neural networks out of theoretical research environments and straight into high-performance, production-grade applications, the company engineers scalable image and video analytics platforms that optimize real-world workflows. Operating a distributed global infrastructure that values collaboration, rigorous software development, and technical excellence, InnovationTeam provides high-agency developers with a frictionless remote environment. The firm empowers its engineering teams with robust compute infrastructures to build category-defining vision systems safely across multi-cloud networks.

Position Overview

We are seeking a highly analytical, mathematically minded Junior AI Engineer – Computer Vision to join our core centralized AI Engineering organization in a full-time remote capacity. Open to qualified specialists resident across India, Egypt, Pakistan, the United Kingdom, the United States, or Germany, this role claims individual operational accountability for designing, training, and deploying vision-based artificial intelligence systems for real-world production setups. Shifting completely away from basic template use or low-scale model testing, you will serve as a core technical anchor, preparing extensive image libraries, optimizing model performance parameters, and serving inference endpoints through containerized microservices. This position requires a disciplined development veteran with a Master’s degree and 5+ years of hands-on computer vision engineering background who manipulates deep learning layers fluidly, programs concurrent data flows smoothly, and maintains pristine code reproducibility under compressed sprint schedules.

Key Responsibilities

• Computer Vision Model Development: Design, train, and optimize scalable deep learning models for complex image and video analysis, ensuring exceptional inference accuracy in live environments.
• Neural Network Pipeline Construction: Implement robust, production-ready solutions for real-time object detection, image classification, multi-class segmentation, and tracking natively utilizing AI Engineer toolsets.
• Dataset Engineering and Management: Oversee data preparation tasks across extensive capture layers, leading data cleaning, manual or programmatic labeling, and complex data augmentation matrices.
• Model Performance and Speed Optimization: Profile and tune neural network weights natively leveraging Computer Vision architectures to maximize GPU performance, minimize latency, and scale inference speed.
• Containerized Production Deployment: Deploy verified machine learning model endpoints into multi-tenant cloud ecosystems, wrapping systems inside secure RESTful APIs and containerized Docker services.
• Cross-Platform Infrastructure Integration: Wire standalone computer vision microservices seamlessly into broader enterprise AI platforms, predictive data lakes, and centralized analytics dashboards.
• Code Reproducibility and Documentation: Maintain meticulous system documentation, authoring deployment runbooks and enforcing high code quality standards via version control channels.
• Cross-Functional Agile Collaboration: Partner peer-to-peer alongside internal software engineers, data scientists, and product management cells to translate business requirements into technical architecture goals.

Required Skills & Qualifications

• 5+ years of verified professional history running advanced machine learning engineering, deep learning application development, computer vision system prototyping, or technical AI consulting.
• Deep, authoritative technical command of modern convolutional neural network (CNN) structures, mathematical loss functions, and state-of-the-art vision models.
• Expert-tier programming proficiency building, training, and adjusting deep learning layers natively utilizing AI Engineer frameworks including PyTorch or TensorFlow, paired with Python and OpenCV.
• Production-tested experience configuring object detection and segmentation grids natively leveraging Computer Vision toolsets (explicitly including YOLO or Detectron2).
• Practical operational familiarity navigating containerization engines, basic MLOps practices, version control tracking, and remote cloud or on-premises deployment environments using Docker.
• Outstanding verbal and written communication mechanics in fluent English, with an absolute capacity to interact professionally across distributed cross-functional technology groups.
• Academic Baseline Qualifications: A formal Master’s degree from an accredited institution specializing in Computer Science, Software Engineering, Artificial Intelligence, or a closely related quantitative science discipline.
• Location Context: Parameters open exclusively to qualified engineers base-stationed permanently and resident within **India, Egypt, Pakistan, the United Kingdom, the United States, or Germany** to execute engineering duties under a 100% remote arrangement.

Preferred Strategic Indicators (Nice to Have)

• Prior commercial history engineering video analytics infrastructure, real-time streaming inference networks, or multi-threaded hardware-accelerated capture applications.
• Exposure to cutting-edge Vision Transformers (ViTs), multimodal AI integrations, or custom layer fine-tuning models.
• Hands-on familiarity with cloud ecosystem architectures, showcasing operational background using OCI, AWS, Azure, or Google Cloud Platform (GCP).
• Background developing software applications tailored to domains including healthcare diagnostics, smart cities, or industrial automation.

What We Offer

• The exceptional professional canvas to directly direct, shape, and code-engineer the foundational computer vision systems and video analytics pipelines power-routing real-world industrial deployments globally.
• Highly competitive, capability-benchmarked full-time baseline compensation packages calibrated precisely to evaluate and reward your deep learning authority and model execution speed.
• Profound work-from-home remote parameters providing an elite digital workplace, complete scheduling trust, and zero physical geographic office commuting friction across multiple allowed countries.
• Direct, uncompromised access to high-performance **GPU infrastructure clusters** and the latest enterprise-grade AI toolkits.
• A highly collaborative, flat engineering-focused work culture that strips away bureaucratic layers to maximize your individual product impact and advanced AI exposure.