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Syed Anser Zaidi

@syedanserzaidi

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ML Engineer building and operating production AI systems across healthcare and fintech.

United States

Message

What I'm looking for

I’m looking to build and operate production AI systems—reliable, scalable, and close to real users. I want ownership of orchestration, MLOps/GenAIOps, and observability so models ship safely and deliver measurable impact.

I’m an ML Engineer with 10+ years building and operating production AI systems across healthcare, fintech, and large-scale platforms. I focus on taking models from experimentation into reliable, scalable services with workflow orchestration, automation, and day-to-day operational ownership.

I enjoy working close to real users and business problems, and I’m at my best when I translate complex ML ideas into practical, maintainable systems that deliver measurable impact. I’ve led MLOps and GenAIOps practices that connect model lifecycle management, prompt changes, CI/CD, and observability so teams can ship updates safely and operate AI systems day to day.

Across AWS-native microservices on Kubernetes, I’ve designed event-driven agent workflows, LLM-based stateless services, and semantic retrieval with OpenSearch vector indexing. I also build large-scale pipelines (Spark, Glue, SageMaker, Redshift, SQL) with strong monitoring and operational visibility (Prometheus, Grafana, CloudWatch, ELK) to improve inference performance, alerting, and system health.

Experience

Work history, roles, and key accomplishments

ML Engineer

Techclomate

Jan 2023 - Jun 2026 (3 years 5 months)

Designed and operated cloud-native AI platforms on AWS, building microservices deployed on Kubernetes (EKS) for real-time intelligence and alerting in healthcare environments. Built LLM/agent-style services with event-driven workflows, semantic retrieval, orchestration (AWS Step Functions), and infrastructure/deployment/monitoring using Terraform, Docker/ECR, GitOps, and Prometheus/Grafana.

AI Engineer

Hexagon

Oct 2017 - Dec 2022 (5 years 2 months)

Designed and operated cloud-native ML platforms on AWS to support real-time risk/decisioning and event analytics. Delivered containerized ML services on Kubernetes, orchestrated ML workflows with AWS Step Functions, built scalable pipelines with Spark/Kinesis/Kafka, and implemented monitoring, CI/CD, and production-ready REST APIs.

AWS Kubernetes EKS Docker Microservices AWS Step Functions Spark EMR Amazon Kinesis Kafka Terraform Monitoring Prometheus Grafana ELK Stack S3 EC2 RDS PostgreSQL IAM Lambda Cloudwatch Jenkins Flask CI CD

Backend Developer

Medzah Industries

Jun 2014 - Sep 2017 (3 years 3 months)

Designed and developed RESTful backend APIs using Python frameworks and built containerized services for scalable deployments. Deployed and operated services on Kubernetes for AWS with CI/CD automation and AWS infrastructure monitoring.