Splunk Developer – Machine Learning & Observability Expert

Position Overview

We are seeking an experienced Splunk Developer to join Enterprise Monitoring team. The ideal candidate will have 6-8 years of hands-on experience with Splunk, including search optimization, machine learning capabilities, and deep technical expertise in log analysis and monitoring solutions.

Key Responsibilities

1. Machine Learning & AIOps

• Design and implement ML-based monitoring solutions using Splunk’s ML Toolkit (MLTK) .
• Build predictive and anomaly detection models for infrastructure metrics (CPU, memory, latency, etc.).
• Develop custom ML use cases —such as log clustering, failure prediction, and capacity forecasting.
• Optimize real-time analytics for large-scale datasets (millions of events / sec).

2. Splunk Observability & Unified Dashboards

3. Search Optimization & Scalability

4. Automation & Advanced Analytics

Mandatory Skills

✅ 6-8 years of Splunk development with proven ML use cases (anomaly detection, forecasting, clustering).

✅ Hands-on Splunk Observability Cloud (SignalFX / APM / IM / Log Observer) .

✅ Experience building unified dashboards for infrastructure (servers, Kubernetes, cloud, network) .

✅ Strong Python for ML (Pandas, Scikit-learn, TensorFlow / PyTorch is a plus) .

✅ Search optimization at scale (data models, accelerated reports, summary indexing) .

✅ Familiarity with DevOps practices (CI / CD pipelines, Terraform, Ansible).

✅ Experience with OpenTelemetry, Prometheus, and distributed tracing.

✅ Knowledge of IT operations, SRE (Site Reliability Engineering), and incident management.

🔹 Splunk certifications (MLTK, Observability, Core Certified Power User) .

🔹 Knowledge of MLOps pipelines (model training, deployment, monitoring).

🔹 Experience with OpenTelemetry, Prometheus, and Grafana integrations .

Why This Role?

This is not just a Splunk admin role —we need someone who can :

🔷 Build AI-driven monitoring to predict failures before they happen.

🔷 Turn observability data into actionable insights with ML-powered dashboards.

🔷 Optimize performance across hybrid cloud, containers, and legacy systems .

If you’ve built ML models in Splunk and designed observability solutions for complex environments, this role is ideal for a Splunk expert who can optimize performance, enhance observability, and implement AI-driven monitoring solutions to improve system reliability and efficiency