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I’m a Master’s student in Artificial Intelligence at Monash University with a strong engineering background in Electrical and Computer Systems Engineering. I build end-to-end, production-grade software and AI-powered systems, spanning LLM-enabled workflows, backend platforms, data pipelines, and real-time integrations. I also enjoy robotics and computer vision work—optimizing ROS2 navigation and perception pipelines for field reliability, and shipping solutions that work under real constraints. I’m currently focused on contributing to AI engineering teams that tackle practical problems, using tools like Python, TypeScript, ROS2, OpenCV/YOLO, and LLM APIs to deliver reliable outcomes.…I’m a Master’s student in Artificial Intelligence at Monash University with a strong engineering background in Electrical and Computer Systems Engineering. I build end-to-end, production-grade software and AI-powered systems, spanning LLM-enabled workflows, backend platforms, data pipelines, and real-time integrations. I also enjoy robotics and computer vision work—optimizing ROS2 navigation and perception pipelines for field reliability, and shipping solutions that work under real constraints. I’m currently focused on contributing to AI engineering teams that tackle practical problems, using tools like Python, TypeScript, ROS2, OpenCV/YOLO, and LLM APIs to deliver reliable outcomes.

Harshmay prasad

AI Engineer, Data Scientist, Data Analyst, +4

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I’m a Master’s student in Artificial Intelligence at Monash University with a strong engineering background in Electrical and Computer Systems Engineering. I build end-to-end, production-grade software and AI-powered systems, spanning LLM-enabled workflows, backend platforms, data pipelines, and real-time integrations. I also enjoy robotics and computer vision work—optimizing ROS2 navigation and perception pipelines for field reliability, and shipping solutions that work under real constraints. I’m currently focused on contributing to AI engineering teams that tackle practical problems, using tools like Python, TypeScript, ROS2, OpenCV/YOLO, and LLM APIs to deliver reliable outcomes.…I’m a Master’s student in Artificial Intelligence at Monash University with a strong engineering background in Electrical and Computer Systems Engineering. I build end-to-end, production-grade software and AI-powered systems, spanning LLM-enabled workflows, backend platforms, data pipelines, and real-time integrations. I also enjoy robotics and computer vision work—optimizing ROS2 navigation and perception pipelines for field reliability, and shipping solutions that work under real constraints. I’m currently focused on contributing to AI engineering teams that tackle practical problems, using tools like Python, TypeScript, ROS2, OpenCV/YOLO, and LLM APIs to deliver reliable outcomes.

Available to hire

I’m a Master’s student in Artificial Intelligence at Monash University with a strong engineering background in Electrical and Computer Systems Engineering. I build end-to-end, production-grade software and AI-powered systems, spanning LLM-enabled workflows, backend platforms, data pipelines, and real-time integrations.

I also enjoy robotics and computer vision work—optimizing ROS2 navigation and perception pipelines for field reliability, and shipping solutions that work under real constraints. I’m currently focused on contributing to AI engineering teams that tackle practical problems, using tools like Python, TypeScript, ROS2, OpenCV/YOLO, and LLM APIs to deliver reliable outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI and Automation Engineer at Eleno Melbourne

May 1, 2026 - Present

Engineered Eleno’s internal operations platform end to end (Next.js, React, TypeScript, Supabase/PostgreSQL). Streamlined timesheets, approvals, finance planning, and referrals for four distinct user roles. Designed a robust data model and security architecture with role-based access control (RBAC), server-side authentication, and authorization-checked server actions to protect all data mutations. Implemented timezone-aware payroll cycle logic and third-party REST API integrations (ClickUp), enabling accurate real-time data syncing across active projects. Shipped production features with AI-assisted development workflows (Claude Code, agentic coding tools), reducing featured delivery time by 30% versus prior cycles. Managed quality and delivery with Vitest/Playwright E2E tests, GitHub Actions CI/CD, and continuous deployments to Vercel, cutting release defects by double-digit percentages.

Teaching Associate at Monash University (Clayton)

February 1, 2026 - Present

Delivered labs across five ECSE units (ECE2131, ECE2071, ECE2072, ECE2191, ECE3161), supporting consistent pass rates above 90% across cohorts. Taught analogue and digital circuit analysis, semiconductors, op-amps, C programming, data structures, probability, and circuit simulation to cohorts of 50+ students, improving average lab scores by 15%. Provided one-on-one and group support for lab work, assignments, and exam preparation, achieving student feedback ratings above 4.7/5 for clarity on complex concepts.

Summer Research Student at Monash University

November 1, 2025 - November 17, 2025

Developing an evidence-based AI predictor, applying machine learning and research skills to analyse and model real-world data for accurate forecasting.

Summer Research Student at Monash University (Melbourne)

October 1, 2025 - June 1, 2026

Engineered an evidence-based AI predictor using machine learning to model real-world aged care data, increasing forecast accuracy for resident demand and staffing decisions. Collaborated with stakeholders to define predictor requirements and validate model outputs, improving operational decision-making speed and alignment with care service needs. Optimized cleaning, transformation, and integration of messy real-world datasets to enhance data quality, reduce model error rates, and improve performance stability across aged care scenarios.

Automation Team Member at Monash Nova Rover (Melbourne)

September 1, 2025 - Present

Led development of perception, navigation, and decision-making for an autonomous rover using computer vision and path planning. Optimized ROS navigation and detection pipelines to run faster on constrained rover hardware, reducing processing latency and increasing real-time frame rates during autonomous runs. Achieved 86 points in the University Rover Challenge 2026 autonomous task (highest task score at the competition) and placed 3rd overall at the Australian Rover Challenge 2026, receiving the Best Engineering Design Award.

Shift Supervisor at Nando’s

September 1, 2025 - November 17, 2025

Contributed to the automation and programming of the Mars rover, collaborating with team members to optimize performance, troubleshoot systems, and meet project deadlines efficiently.

AI Engineer at Zen (Melbourne)

July 1, 2025 - November 1, 2025

Built a 5 degrees-of-freedom servo-controlled robotic arm with ±1° positioning accuracy and a 30–40 cm working envelope. Implemented a computer vision pipeline using YOLO and OpenCV for 90% real-time object detection accuracy. Built an integrated SLAM navigation system combining camera-based mapping and a 4-sensor ultrasonic array for autonomous obstacle avoidance.

AI/Robotics Engineer at Zen.

July 1, 2025 - November 17, 2025

Developed a 5 degree-of-freedom robotic arm with servo-controlled joints, achieving ±1° positioning accuracy and 30–40 cm working envelope for autonomous tasks. Implemented a computer vision pipeline using YOLO and OpenCV, achieving 90%+ real-time object detection accuracy. Built an integrated SLAM navigation system combining camera-based mapping and a 4-sensor ultrasonic array for autonomous obstacle avoidance.

AI Engineer at Atlas Robotics and Technology

July 1, 2025 - Present

Internship focusing on AI engineering, pattern recognition, and development of data-driven models to improve robotic perception and automation; contributed to productivity improvements and enhanced object detection through innovative models.

Student Fellow at Startmate (Melbourne)

June 1, 2025 - August 1, 2025

Selected for Startmate’s competitive student fellowship: completed a two-week immersive accelerator and delivered 100% of startup ideation and venture-building milestones. Led and pitched a startup solution to mentors, operators, and VC leaders, securing actionable feedback from 10+ stakeholders. Drove collaboration with cross-functional cohort peers to refine venture concepts and validate product-market fit assumptions through structured testing sessions.

Prompt Engineer, Outlier Australia at Outlier Australia (Australia)

October 1, 2024 - September 1, 2025

Assessed over 30 AI-generated math responses, improving accuracy and relevance by 30%. Crafted and reviewed 20+ math questions, driving a 25% improvement in model precision. Reduced content revision cycles by 30% through systematic evaluation of AI outputs.

AI Model Trainer at Outlier AI

October 1, 2024 - November 17, 2025

Assessed and improved AI-generated responses, increasing model accuracy by 15%. Evaluated content for factual correctness, ensuring 90% alignment with mathematical standards.

AI Model Trainer at Outlier AI

October 1, 2024 - Present

Assessed and improved AI-generated responses, enhancing accuracy by 15% using data-driven optimization and NLP techniques.

Research Student at Monash University

June 1, 2023 - June 1, 2023

Developed algorithms for LiDAR and ROS integration, resolving 5 compatibility issues. Increased system efficiency by 20% using Python and ROS optimization. Conducted literature review and data modelling, reducing tracking inconsistencies by 40%.

Shift Supervisor at Nando's

September 1, 2022 - Present

Led a team, ensured health and safety standards, and implemented data-driven scheduling to improve operational efficiency.

Research Student at Monash University (Clayton)

July 1, 2022 - June 1, 2023

Developed a new algorithm for LiDAR and ROS integration, resolving 5 compatibility issues. Increased system efficiency by 150% using ROS optimization and reduced testing delays by 200%. Reduced tracking inconsistencies by 40% through data modeling and algorithm refinement.