3 Days Left) Scientist
2 weeks ago
JOB DESCRIPTION
This role combines advanced AI/ML expertise with IT operations (Infrastructure, Networks, Applications, Digital integrated experience) to build scalable solutions for automating processes like incident management, resource allocation, and infrastructure optimization. Key objectives include:
- Reducing mean time to resolution (MTTR) through predictive maintenance and AI-driven anomaly detection.
- Deploying Gen AI for log analysis, code generation, and automated documentation using frameworks like GPT-4, LangChain, or Vertex AI.
- Designing Agentic AI systems where autonomous agents collaborate to execute tasks (e.g., auto-scaling, security threat mitigation).
- Integrating AI with DevOps pipelines (CI/CD, Kubernetes) and IT tools (ServiceNow, Ansible, Terraform).
RESPONSIBILITIES
1. AI/ML Model Development:
- Build predictive models for IT automation (e.g., incident prediction, resource optimization).
- Implement reinforcement learning for self-healing infrastructure and auto-scaling.
2. Gen AI Integration:
- Develop LLM/RAG-based conversational AI for automated code reviews, log parsing, and knowledge-base curation.
- Fine-tune models for domain-specific tasks (e.g., IT ticket classification, root-cause analysis).
3. Agentic AI Design:
- Architect multi-agent systems to automate workflows like ticket routing, patch management, and compliance checks.
- Enable real-time collaboration between AI agents and human operators.
4. Automation Pipeline Engineering:
- Deploy AI models into production using MLOps tools (MLflow, Kubeflow) and orchestration platforms (Airflow, Prefect).
- Ensure seamless integration with DevOps pipelines and observability tools (Datadog, Splunk).
5. Governance & Ethics:
- Enforce transparency, fairness, and compliance (GDPR, SOC2) in AI-driven workflows.
- Monitor model drift and performance in production systems.
QUALIFICATIONS
- 5+ years in data science, with 3+ years focused on AI-driven IT automation.
- Proficiency in Python, PyTorch/TensorFlow, LLM frameworks, and cloud platforms (AWS/GCP/Azure).
- Advanced degree in Computer Science, Data Science, or related fields. Certifications in AI/ML or MLOps (e.g., AWS ML Specialty, Google Cloud ML Engineer) preferred.
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