Computer Vision (Video Analytics) Dev

Job Title : Computer Vision (Video Analytics) Dev

Location: Kondapur HYD

Experience: 3-5 years

Role SUMMARY

Own the end-to-end technical architecture of the platform — from IP67 edge camera capture through computer vision inference to the SaaS dashboards used by kitchen operators, aggregators, and FSSAI regulators. This is a hands-on leadership role for someone who has already taken at least 2–3 video analytics products from zero to production, ideally in kitchen, utility, or industrial/environmental-safety domains where wastage, hygiene, and safety KPIs were the core deliverable.

KEY RESPONSIBILITIES

• Architecture ownership — design the full edge-to-cloud pipeline: IP67 camera capture, RTSP ingestion, edge inference nodes, MQTT-based event orchestration, and the cloud aggregation and dashboard layer.
• SaaS platform — direct development of the web application across both frontend and backend, covering the operator dashboard, aggregator API layer, and FSSAI regulator view.
• MLOps & model lifecycle — own model versioning, CI/CD for model deployment, automated retraining pipelines, and continuous production monitoring for drift, accuracy decay, and latency.
• KPI pipelines — define and enforce data-pipeline standards for hygiene, wastage, and environmental-safety KPIs (PPE compliance, cross-contamination, spill/pest detection, portion variance, storage segregation).
• Performance & reliability — set and hold the team to technical SLAs such as sub-2-second inference latency and 99.9% system uptime.
• Cloud & DevOps — evaluate and implement AWS or GCP infrastructure for secure, multi-tenant deployment across hundreds of outlets; build containerization, CI/CD, and observability practices.
• Team leadership — lead and mentor the Data Scientist and the three interns; run technical reviews and unblock delivery.
• Compliance by design — ensure the architecture meets DPDP Act 2023 and FSSAI requirements, including edge-anonymization of facial data for the Smilometer/Trust Score modules.
• Founder support — partner with the founders on technical due diligence for fundraising conversations and enterprise or regulator pilots.

REQUIRED SKILLS & QUALIFICATIONS

• 5–8 years of software/ML engineering experience, including at least 2–3 video analytics projects taken from concept to live production.
• Prior experience in kitchen, utility, industrial, or environmental-safety monitoring domains strongly preferred — especially wastage tracking, hygiene compliance, or safety KPIs.
• Strong full-stack development ability — modern frontend framework (React or equivalent) and backend (Node.js/Python).
• Hands-on MLOps experience: model packaging, deployment pipelines, and monitoring/alerting for model drift.
• Solid grounding in computer vision fundamentals (object detection, action recognition), even without daily hands-on model training.
• Experience designing multi-tenant SaaS architectures — auth, role-based access, API design, dashboarding.
• Comfortable working with edge-compute devices and video streaming protocols (RTSP, MQTT).

PREFERRED / NICE-TO-HAVE

• Working knowledge of AWS or GCP — compute, storage, IoT services, and managed ML platforms.
• Experience with Docker/Kubernetes and CI/CD pipelines.
• Exposure to regulated, compliance-heavy domains such as food safety, healthcare, or utilities.
• Prior 0-to-1 or early-stage startup product-building experience.

Pay: ₹500,000.00 - ₹800,000.00 per year

Experience:

• Video Analytic: 3 years (Preferred)
• Data science: 5 years (Preferred)

Location:

• Hyderabad, Telangana (Preferred)

Work Location: In person