Applied Ai Engineer Job at Everseen (Timișoara)

Job Description

As an Applied AI Engineer – Edge AI & Computer Vision, you will play a pivotal role in developing intelligent systems that operate efficiently on edge devices. You will design, refine, and own robust Machine Learning (ML) and Computer Vision (CV) systems, with a direct focus on edge deployment, automated pipelines, performance optimization, and seamless software integration. This role bridges the gap between cutting-edge research and real-world deployment, refactoring and hardening AI models to meet strict latency, scalability, and resource constraints on specialized edge hardware.

Job Responsibility

Own and deliver key Machine Learning and Computer Vision components or features of a project
Design, execute, and deliver robust applications that interface with edge devices
Support graduated AI solutions throughout their production lifecycle, ensuring continuous reliability
Refine, refactor, and harden existing AI implementations to meet high-quality production standards
Design and implement targeted initiatives to optimize system efficiency, real-time performance, and pipeline output
Apply model optimization techniques (e.g., quantization, pruning, and latency tuning) for specialized, resource-constrained edge devices
Develop advanced-scope tools to automate research and development processes and enhance workflow efficiency
Manage production infrastructure for model training and serving, incorporating modern MLOps workflows and pipelines
Identify novel solutions and take an active role in designing modular application units
Expand on experimental results presented by research teams and successfully transition them from research to robust production environments

Requirements

Ideally 2–3 years of practical experience working on Machine Learning and Computer Vision systems deployed at the edge
Proven experience in moving machines learning models successfully from research environments to high-performance, real-time production environments
Bachelor’s degree in computer science, Engineering, Machine Learning, Mathematics, or a closely related technical field
Master’s degree in a related technical domain is highly preferred
Exceptional practical problem-solving and algorithmic skills
Highly analytical and able to identify trends, make data-driven decisions, and think critically to construct efficient solutions
Proactive and highly adaptable
comfortable navigating ambiguity in a fast-paced, rapidly evolving ML environment
Strong communication and teamwork skills
capable of aligning technical consensus and influencing peers with technical expertise while beginning to act as a mentor
Deep understanding of ML algorithms, tuning, training, and evaluation procedures, combined with a strong grasp of classical computer vision concepts
Hands-on experience with hardware/resource optimization, deploying models on specialized/embedded edge devices, and optimization of real-time systems
Solid understanding of software engineering principles, version control (Git), and CI/CD pipelines
Ability to integrate and maintain strict standards of code and model quality for long-term maintenance
Strong proficiency in Python OR expert-level proficiency in a low-level/systems programming language (e.g., C/C++) with a willingness to learn Python
Working knowledge of video streaming, processing, decoding, and format handling
Familiarity with major cloud platforms and data orchestration workflows

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Applied Ai Engineer

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