Het Patel

Software Engineer

Palo Alto, California, United States1 yr 5 mos experience

Key Highlights

Expert in scalable distributed systems and cloud-native architectures.
Hands-on experience with leading tech companies like Tesla and Samsung.
Proficient in CI/CD automation and data/ML pipelines.

Stackforce AI infers this person is a Backend-heavy Infrastructure Engineer with expertise in scalable systems and data processing.

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Skills

Core Skills

Software EngineeringQuality AssuranceInfrastructureMonitoringDistributed SystemsMlopsMicroservicesData ProcessingData EngineeringDevops

Other Skills

AWSAirflowAlgorithm DesignAlgorithm DevelopmentAlgorithmsAmazon Web Services (AWS)Apache AirflowApache KafkaApache SparkApplication Programming Interfaces (API)AutomationBack-End Web DevelopmentC (Programming Language)C++C/C++

About

I’m a Software Engineer specializing in designing and building scalable distributed systems, infrastructure, Test/QA, and data/ML pipelines. I focus on backend and cloud-native architectures that enable high performance, reliability, and fault tolerance across complex, large-scale environments. I have gained hands-on experience at leading companies including Samsung, Nokia, Altair, and Medtronic. My work spans containerized microservices, CI/CD automation, test frameworks, observability, and big data pipelines—leveraging technologies such as Python, Go, Java, Docker, Kubernetes, AWS, Kafka, Spark, Airflow, MLflow, and Linux. Passionate about distributed systems and data/ML infrastructure, I’m always looking for smarter ways to automate, troubleshoot, and build resilient scalable solutions. I’d love to collaborate or discuss new opportunities. Feel free to message me here on LinkedIn or reach out to me at "het.patel@alumni.scu.edu".

Experience

Tesla

Software Engineer

Sep 2025 – Present · 6 mos · Palo Alto, California, United States · On-site

Tesla AI • Autopilot • Infrastructure Stability • CI • Observability

Medtronic

Software Engineer

Oct 2024 – Sep 2025 · 11 mos · Los Angeles, California, United States · Hybrid

Software Testing, Infrastructure, CI/CD, Automation, Quality Assurance.
Test scenarios designing, Anomaly detection, Story verification, Jira.

Software TestingInfrastructureCI/CDAutomationQuality AssuranceSoftware Engineering

Altair

Technology Consultant

May 2024 – Oct 2024 · 5 mos · Santa Clara, California, United States · Remote

Solution Deployment, Client Facing, Linux/Windows Administration, Docker, Monitoring, Logging.
Built, deployed, and automated infrastructure provisioning and containerization (Python, Docker) to streamline manual operations.
Administered and troubleshot Linux systems, VMs, networks, DNS, and storage for distributed client environments.
Deployed an observability stack (Prometheus, Alertmanager, Loki, cAdvisor, Grafana) to improve system monitoring and alerting.
Improved system reliability and incident response for multi-node distributed setups.

Solution DeploymentLinux/Windows AdministrationDockerMonitoringLoggingSoftware Engineering+1

Nokia

Software Engineer

Sep 2023 – Dec 2023 · 3 mos · Sunnyvale, California, United States · Hybrid

Infrastructure, MLOps, LLMs, Multiprocessing, Microservices, REST APIs, Docker, CI/CD, Testing.
Developed LLM based distributed microservices (Python, Docker, Flask) with scalable GitLab CI/CD pipelines and REST APIs for data processing.
Optimized CPU-based LLM processing on large VMs with multiprocessing and multithreading to lower compute costs. Used gRPC for efficient data transfer between microservices.
Instrumented tracing and observability with OpenTelemetry, Prometheus, and Grafana for Kubernetes-deployed services.
Load-tested and tuned Kafka-based pipelines for high-throughput data flow and resilience under real-world conditions.

MLOpsMicroservicesREST APIsDockerCI/CDTesting+1

Samsung r&d institute india - bangalore

Software Engineer

Jan 2022 – Jul 2022 · 6 mos · Bengaluru, Karnataka, India · Remote

DevOps, AWS, Python, Spark, Airflow, Data Engineering, Linux.
Designed and deployed parallel ETL pipelines using Apache Spark (Python) and Airflow DAGs to improve data processing efficiency.
Automated ingestion of large-scale ad data to AWS (S3, EC2) using Airflow and Python.
Containerized pipelines with Docker and worked with Kubernetes orchestration and CI/CD for robust deployment.
Diagnosed Linux system performance issues and improved reliability of distributed data pipelines.

DevOpsAWSPythonSparkAirflowData Engineering+1