Machine Learning Graph Systems Engineer

2 days ago

Bengaluru, Karnataka, India Gloify Full time

About Gloify

Gloify is a cutting-edge technology company that harnesses the power of artificial intelligence and machine learning to drive innovation.

Salary Range: $120,000 - $180,000 per year

Job Description:

We are seeking an exceptional AI/ML Graph Systems Engineer to join our team. As a key member of our engineering group, you will design, develop, and deploy scalable machine learning systems using graph databases such as Neo4j.

Key Responsibilities:

  • Design and develop machine learning models and algorithms for production environments, ensuring scalability and robustness.
  • Leverage graph databases to model, query, and analyze data relationships in large-scale connected data systems.
  • Build and optimize ML pipelines for production-ready solutions that can handle high volumes of data in real-time.
  • Develop rule-based systems and work with complex logical inference engines to handle business logic, constraints, and decision-making processes.
  • Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into existing products and platforms.
  • Implement algorithms for entity resolution, recommendation engines, fraud detection, or other graph-related tasks using graph-based ML techniques.
  • 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 in model performance and adaptability.
  • Participate in architectural decisions, ensuring efficient use of graph databases and ML models.
  • Stay up-to-date with the latest advancements in AI/ML research, particularly in graph-based machine learning, reasoning systems, and logical AI.

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • 1+ years of experience in AI/ML engineering or a related field, with hands-on experience in building and deploying ML models in production environments and self-made projects using graph database.
  • Proficiency in Neo4j or other graph databases, with a deep understanding of Cypher query language and graph theory concepts.
  • Strong programming skills in Python, Java, or Scala, along with experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Experience with machine learning pipelines and tools like Airflow, Kubeflow, or MLflow for model tracking and deployment.
  • Hands-on experience with rule engines or logic programming systems (e.g., Drools, Prolog).
  • Experience with cloud platforms such as AWS, GCP, or Azure for ML deployments.
  • Familiarity with containerization and orchestration technologies like Docker and Kubernetes.
  • Experience working with large datasets, SQL/NoSQL databases, and handling data preprocessing at scale.

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