Skip to main content
Sara Sehgal

Sara Sehgal

Computer Engineering graduate with production experience in Python, backend and full-stack development, CI/CD, and cloud data pipelines

Talent
TorontoMember since August 17, 2026
PythonNumPyPandasSQLREST APIsFastAPIReactPostgreSQLCI/CDGitHub ActionsGitData pipelinesETLOpenAIAnthropicGeminiRAGLangGraphChromaDBNLPRecommendation systemsKerasTensorFlowLSTM
·

Hire this person

Send a job offer directly to this candidate

PythonNumPyPandasSQLREST APIs

About

Computer Engineering graduate with production experience in Python, backend and full-stack development, CI/CD, and cloud data pipelines, plus hands-on LLM, RAG, agent, NLP, and recommendation projects. Builds reliable services and grounded AI systems with evaluation and testing. Available for full-time work in Canada.

Experience

Launch Test Engineering Intern at Tesla (2025-05 – 2025-08)

  • Automated CI/CD pipelines in GitHub Actions to deploy version-targeted software releases across offline test systems, adding artifact workflows and regression checks that shortened integration cycles by 2 to 3 days.
  • Implemented an asynchronous Python monitoring daemon that detected and restarted memory-leaking test software during off-hours, using safe timed recovery to prevent false alerts and restore reliable operation.
  • Built a production diagnostic application integrating DAQ/CAN interfaces, NI TestStand, LabVIEW, and SQL/SCADA logging, reducing scrap-inducing failures about 73% and troubleshooting turnaround to under 2 hours.

Controls Engineering Intern at Alcon (2024-01 – 2024-05)

  • Validated a computer-vision inspection system by tuning filters, calibrating exposure through the Pylon SDK, and building SQL-logged datasets, improving defect-detection accuracy 20% with full automation.
  • Developed PLC safety and interlock software in Siemens SIMATIC Step 7, using sequence debugging and I/O force testing to cut execution time 25% for regulated equipment qualification.

NPI Test Engineering Intern at Hero MotoCorp Ltd (New Model Center) (2023-05 – 2023-06)

  • Automated DAQ data pipelines in Python using NumPy and Pandas, applying statistical thresholding and trend analysis to detect anomalies, correlate failure modes, and surface root causes across iterative test conditions.
  • Documented failures and performed root-cause troubleshooting across iterative builds, improving test-rig uptime 30%.

Education

MEng in Computer Engineering (part-time) – University of Toronto, St. George (2026-09)

B.S. in Computer Engineering – University of Illinois, Urbana-Champaign (2026-05)

Skills

backend and full-stack developmentCI/CDand cloud data pipelines

Reviews

Related