Senior AI Engineer

Position Overview:

We are a Data Science team in a leading global company, building end‑to‑end AI solutions that run efficiently on edge devices. We are looking for a Senior AI Engineer with deep experience in AI algorithms, infrastructure, and data processing pipelines, especially in domains involving video processing and hardware‑constrained model deployment. This opportunity is a part-time vendor position (60%) that is fully embedded in the team and offers flexible work hours.

The ideal candidate combines strong algorithmic and ML understanding with hands‑on expertise in data engineering, cloud-based ML workflows, and research infrastructure design. You will own critical components of our data and model pipelines, help shape scalable ML training and evaluation environments, and drive real-world deployment of models on specialized hardware. This is a unique opportunity to influence the next generation of AI on the edge, collaborate with multidisciplinary teams, and build systems that have meaningful impact across the company’s ecosystem.

Role Requirements:

•B.Sc., M.Sc. or Ph.D. in Computer Science, Engineering, or related field.

•Strong background in Machine Learning, Deep Learning, and algorithmic problem‑solving.

•3+ years of professional experience in roles such as AI/ML engineer, algorithms developer, applied researcher.

•Proficiency with cloud platforms, ML infra tools, orchestration frameworks, and training environments (e.g., PyTorch/TensorFlow, Azure Machine Learning, distributed training, containerization).

•Strong coding capabilities in Python and relevant ecosystem tools.

•Demonstrated ability to take systems from ideation to production, preferably with real‑world impact (publications or patents a plus).

•Great communication skills and ability to collaborate with cross‑functional engineering and research teams.

•Preferred: Hands-on experience building data processing algorithms, video processing pipelines, dataset preparation workflows, and automated evaluation systems.

•Preferred: Experience with deploying ML models on resource‑constrained hardware (edge devices, GPUs/NPUs, optimization toolchains).

Role Responsibilities:

•Develop algorithms and models across domains such as Computer Vision and Language Models, with emphasis on production‑ready pipelines.

•Design and implement scalable data processing pipelines, including video preprocessing, feature extraction, dataset generation, and automated validation.

•Build and maintain robust ML training, evaluation, and deployment environments, ensuring reliability and efficiency across cloud and edge targets.

•Optimize models and workflows for performance, latency, and resource efficiency on constrained hardware.

•Collaborate with data scientists and engineering partners to deliver solutions that lead to patents, publications, and successful deployments.

•Ensure high data and model quality through rigorous testing, benchmarking, and monitoring.

•Drive infrastructure and pipeline improvements that elevate our team’s AI development velocity and reliability.

•Contribute to long‑term strategic initiatives and propose innovative solutions to complex system challenges.