Senior Machine Learning Engineer

Skills

Overview:

We’re looking for an experienced and hands-on Senior Machine Learning with deep expertise in computer vision technologies to drive the design, development, and deployment of advanced ML models powering our data integration platform.

In this role, you will be a part of a small, high-performing team focused on computer vision tasks, such as  deep fake detection, semantic segmentation, object tracking, vision language models fine-tuning, etc. You will work closely with engineering and data infrastructure teams to build, optimize, and deploy scalable ML services in production using NVIDIA Triton, Kubernetes, and modern transformer-based architectures.

This position requires a unique combination of machine learning depth and software engineering proficiency to deliver robust, real-time, multimodal ML enrichment capabilities.

Responsibilities:

Proactively do research in the field, conduct models verification, design architectures, build training pipelines, verify on real data and develop high performance services for production-grade deployments in:

• Image/Video Deep Fake detection;

• Vision Language Models fine-tuning;

• Semantic Segmentation;

• Object detection and recognition;

• Representation Learning.

Research and integrate transformer-based and multi-modal model architectures into production pipelines.

Collaborate with platform engineers to deploy ML models via NVIDIA Triton Inference Server and ensure low-latency, scalable serving.

Design and maintain Airflow DAGs for data preprocessing, feature extraction, and model enrichment pipelines.

Ensure continuous improvement of models through retraining, performance monitoring, and data feedback loops.

Contribute to and review production-level code in Python (C++, Golang, Rust knowledge is beneficial).

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Electrical Engineering, or related field
• Demonstrated record of leading ML initiatives from research to production.
• Experience in startups or fast-paced, product-centric teams is highly desirable.