Corsearch

2 Jobs

1,642 Employees

About the Company

Corsearch’s leading Trademark and Brand & Content Protection Solutions are revolutionizing how companies create, monitor, and protect their brands. Over 5,000 businesses worldwide partner with Corsearch to safeguard consumers and their trust in brands — preventing confusion, misrepresentation, and fraud using the hybrid intelligence of advanced AI precision and expert decision of human analysts.

For over 70 years, Corsearch has been providing cutting-edge Trademark Clearance and Protection solutions to the world’s leading corporations, law firms and branding agencies. Corsearch offers an evolving and responsive set of integrated tools for Screening, Search, Watch, Brand Protection, and Content Protection.

Behind the world’s best-known brands, there’s Corsearch.

Listed Jobs

Company Name: Corsearch
Job Title: Machine Learning Engineer
Job Description: **Job title:** Machine Learning Engineer **Role Summary:** Design, develop, and deploy computer vision and NLP models to power image search and content monitoring solutions for brand protection. Work with cross‑functional data science and engineering teams to optimize model accuracy, scalability, and production performance. **Expectations:** - Minimum 3 years professional experience as a Machine Learning Engineer. - Fluent in English (written and spoken). - Proven track record of building and productionizing deep learning models. **Key Responsibilities:** - Build and fine‑tune CNNs, RNNs, Transformers for image recognition, object detection, reverse image search, and image‑text matching. - Develop NLP pipelines for text classification, sentiment analysis, and entity recognition. - Construct scalable data ingestion and preprocessing pipelines for image and text datasets. - Conduct research on state‑of‑the‑art algorithms to improve model accuracy and efficiency. - Monitor in‑service model performance, identify bottlenecks, and propose optimizations. - Collaborate with data scientists, product managers, and infrastructure engineers to integrate ML solutions into production systems. **Required Skills:** - Expertise in TensorFlow, PyTorch, Keras, or CatBoost. - Strong background in computer vision (CNNs, R‑CNNs, YOLO, etc.) and NLP (Transformer variants, BERT, etc.). - Proficiency in image processing, feature extraction, and text preprocessing. - Experience with large‑scale data pipelines (e.g., Spark, Kafka, Airflow). - Knowledge of version control (Git), containerization (Docker), and CI/CD practices. - Excellent analytical, problem‑solving, and communication skills. **Required Education & Certifications:** - Bachelor’s or higher degree in Computer Science, Electrical Engineering, Data Science, or a related field. - Certified Machine Learning or Deep Learning practitioner (e.g., TensorFlow Developer Certificate, Nvidia Deep Learning certification) preferred.

Company Name: Corsearch
Job Title: ML Engineer (Production-focused)
Job Description: **Job Title:** ML Engineer (Production-focused) **Role Summary:** Build, deploy, and maintain scalable machine‑learning models for large‑scale detection and classification. Own the full ML lifecycle—data processing, training, evaluation, deployment, and monitoring—ensuring fast, stable, and reliable production systems. **Expectations:** - Deliver end‑to‑end ML pipelines that meet strict latency, throughput, and reliability targets. - Demonstrate measurable impact (e.g., precision gains, latency reductions, uptime improvements). - Collaborate with software engineering teams to integrate models into a microservice architecture and maintain CI/CD workflows. **Key Responsibilities:** - Design, train, and optimize PyTorch/TensorFlow models for detection, classification, and automation tasks. - Convert trained models into production‑ready services (Docker containers, model servers). - Tune inference performance—latency, memory, and throughput—using profiling and optimization techniques. - Build and maintain automated ML pipelines: data ingestion, preprocessing, validation, deployment, and monitoring. - Implement model versioning, testing, and CI/CD pipelines to ensure reproducible releases. - Monitor model performance in production, trigger retraining or drift mitigation as needed. - Work with infrastructure teams to deploy models on cloud (AWS) or container orchestration (EKS, Lambda). **Required Skills:** - 3+ years as an ML Engineer delivering production models. - Proficient in Python (production‑grade). - Hands‑on experience with PyTorch (preferred) or TensorFlow. - Proven deployment/serving experience (Docker, model servers). - Strong inference optimization (latency, resource usage). - Deep understanding of ML pipeline automation and CI/CD. - Experience with Docker, Kubernetes/containers. - Fluent in English. - Availability in CET‑aligned time zone (CET − 2 to CET + 4). **Nice to Have:** - AWS services: SageMaker, EKS, Lambda, S3. - Experience with high‑throughput/ high‑load systems. - CI/CD tooling for ML. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related technical field (Master’s preferred).