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Correlation and Causality Engineer

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Correlation and Causality Engineer in Others new

  • Makati City, Philippines

Responsibilities

  • Design and implement correlation, causality, root-cause analysis, and inference solutions across logs, metrics, traces, and events.
  • Design, train, evaluate, maintain, and productionize machine learning and statistical models for anomaly detection, time-series analysis, and causal inference.
  • Build LLM-based applications using RAG, agents, tool/function calling, embeddings, and vector stores for incident analysis and knowledge discovery.
  • Select, deploy, fine-tune, and operate AI models and LLMs on local or on-premise infrastructure while managing performance, cost, security, and privacy.
  • Develop scalable services in Java and Python and apply engineering practices including code reviews, testing, documentation, and version control.
  • Define evaluation metrics and processes for the accuracy, reliability, and explainability of AI solutions.
  • Explore and exploit observability data using Prometheus, OpenTelemetry, Loki, and Grafana.
  • Build and maintain CI/CD pipelines and deploy solutions on containerized platforms while contributing to reliability and monitoring.
  • Consult with internal technical and operational teams and communicate complex insights to stakeholders.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience.
  • Strong software development skills in Java and Python with knowledge of software design, testing, and engineering best practices.
  • Proven expertise building data-driven models using machine learning, statistical modeling, time-series analysis, and anomaly detection, with understanding of correlation and causal inference.
  • Hands-on experience with LLMs, prompt engineering, RAG, embeddings, vector databases, agents, and tool-calling frameworks such as LangChain or similar.
  • Experience running and fine-tuning AI models locally or on-premise, including understanding of GPU resources, model selection, and optimization.
  • Proficiency with data and machine learning libraries and frameworks including pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
  • Solid DevOps experience with Git, CI/CD pipelines, Jenkins, and GitLab or GitHub.
  • Working knowledge of Docker, Kubernetes, and observability standards and stacks including Prometheus, OpenTelemetry, Loki, and Grafana.
  • Familiarity with Terraform and cloud platforms such as AWS, Azure, OCI, or GCP is a plus.
  • Strong analytical, problem-solving, communication, collaboration, and stakeholder-management skills.

Benefits

  • Hybrid and flexible working arrangements are available for most employees.
  • The role is based within Avaloq’s global office environment and supports an inclusive, equal-opportunity culture.

Avaloq

Avaloq delivers cutting-edge wealth management technology and services tailored for financial institutions, including private banks, investment managers, and retail banks. With a strong global presence and a commitment to research-led innovation, we empower our clients to elevate their financial ...

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