Machine Learning Expert for Scalable Systems
1 week ago
We are seeking a seasoned AI/ML Engineer to join our team and contribute to the development of cutting-edge machine learning solutions. As an expert in graph databases, you will leverage your skills to build scalable production systems that drive business growth.
About the Role:- Design and deploy machine learning models and algorithms for large-scale production environments, ensuring robustness and scalability.
- Leverage Neo4j and other graph databases to model, query, and analyze complex data relationships.
- Build and optimize ML pipelines using Airflow, Kubeflow, or MLflow, ensuring they are production-ready and handle high volumes of data.
- Collaborate with cross-functional teams to integrate ML solutions into existing products and platforms.
- Implement graph-based ML techniques for entity resolution, recommendation engines, fraud detection, and more.
- Work with large datasets, performing exploratory data analysis, feature engineering, and model evaluation.
- Monitor, test, and iterate on ML models post-deployment to ensure continuous improvement.
- Bachelor's or Master's degree in Computer Science, Machine Learning, or Artificial Intelligence.
- 1+ years of experience in AI/ML engineering, with hands-on experience in building and deploying ML models.
- Proficiency in Neo4j and Cypher query language, with a deep understanding of graph theory concepts.
- Strong programming skills in Python, Java, or Scala, along with experience using ML frameworks like TensorFlow and PyTorch.
- Experience with cloud platforms like AWS, GCP, or Azure for ML deployments.
- Familiarity with containerization and orchestration technologies like Docker and Kubernetes.
- Experience working with large datasets and handling data preprocessing at scale.
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