AI/ ML Engineer- MLOPS
3 days ago
About Giggso
Giggso is an award-winning, Michigan-based AI startup, recognized in the Top 50 Michigan Startups of 2023 & 2024. Founded in 2017, we deliver a unified platform for AI agent orchestration, governance, and observability, simplifying complex enterprise workflows.
Our solutions extend to model risk management, security, and blockchain enablement, ensuring trustworthy AI across diverse industries. By automating operations and providing real-time monitoring, Giggso drives cost savings and boosts organizational intelligence.
We champion responsible AI to help businesses optimize decision-making and enhance customer experiences at scale.
Resposnibilties
• Design and implement end-to-end ML pipelines for training, validation, and deployment.
• Integrate pipelines with CI/CD tools for automated builds and deployments.
• Ensure version control for models, datasets, and configurations. Implement security best
practices and ensure compliance with regulatory standards.
• Deploy models (safe roll outs), Optimize inference performance (latency, throughput) and ensure high availability
• Set up model performance monitoring, implement infrastructure observability, configure alerting and incident response for model degradation or failures
• Enforce IAM policies, network isolation, and encryption (at rest and in transit).
• Prepare ML environments and pipelines for Vulnerability Assessment & Penetration Testing, address findings, and maintain remediation logs.
• Integrate SAST/DAST scans into pipelines for vulnerability detection.
• Implement model registry with approval workflows.
• Ensure adherence to IRDAI guidelines, DPDP Act, and ISO 27001; maintain audit artifacts.
Ensure model cards, data lineage, and bias/fairness checks are documented
• Support Responsible AI guardrails for LLMs (prompt injection defense, toxicity filters)
• Provide periodic security posture reports and evidence of compliance for internal and external audits
Requirements:
• At least 3 years of experience in AI/ML or MLOps (≥2 years in production-like settings for
respective role).
• Strong Python engineering (typing, testing, packaging) for AI/ML roles
• Strong experience in DevSecOps practices for ML pipelines, including CI/CD automation,
container security, vulnerability scanning, and Infrastructure as Code for cloud environments for MLOps
• Proven experience in cloud platforms (GCP preferred) and container orchestration (Kubernetes).
• Familiarity with compliance frameworks (IRDAI, DPDP Act, ISO and VAPT readiness.
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