AI/ML Platform Support Engineer (fte/onsite)

AI/ML Platform Support Engineer

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a AI/ML Platform Support Engineer (FTE/Onsite) to join our team in Charlotte, North Carolina (US-NC), United States (US).

Job Duties and Responsibilities

We are seeking a talented AI/ML Platform Support Engineer to join our dynamic team. In this role, you will be responsible for supporting the platforms used to develop AI/ML infrastructure and solutions.

Core Technical Skills

• Vector Databases: Hands-on experience with Elasticsearch or similar; understanding of similarity search, indexing strategies, and embedding management.
• Linux Systems: Strong command-line skills; shell scripting; system-level monitoring and debugging.
• Python Programming: Proficient in automation scripting; experience in building AI models, data pipelines, and OpenAI integrations.
• Big Data Technologies: Familiarity with Hadoop-based platforms like MapR and Hortonworks.

AI Platform & Production Support

• Experience supporting predictive AI workloads in production.
• Troubleshooting across data ingestion, model inference, and deployment layers.
• Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes).
• On-call support for GenAI and predictive pipelines (1 week every 6–8 weeks).
• Understanding of enterprise disaster recovery (DR) solutions including backup and restore.

Observability & Monitoring

• Ability to define and implement observability strategies for AI systems.
• Experience with tools such as Splunk, Grafana, ELK stack, OpenTelemetry.
• Proactive monitoring of model failures, latency, and system health.

Bonus Qualifications

• Multi-cloud Experience: Exposure to GCP and Azure environments.
• Data Science Lifecycle: Involvement in full-cycle projects including problem definition, data exploration, modeling, evaluation, training, scoring, and operationalization.
• MLOps Principles: Understanding of model lifecycle management and collaboration with data scientists to deploy solutions.

Desired Qualifications

• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication and collaboration skills to work effectively with cross-functional teams.
• 2+ years of Python development experience
• 3+ years of Linux experience