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AI & Computer Vision Engineer

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Onsite

AI & Computer Vision Engineer

Techasoft Pvt Ltd

AI & Computer Vision Engineer

Skills

MongoDBDeep LearningDockerReactPythonPyTorchTensorFlowPostgreSQLMySQLKafkaRedisData AnalysisAIAWSLinuxComplianceAzure

14 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

14 October 2026

What they need


Job highlights

  • Bangalore
  • Full Time
  • Starts immediately
  • 2+ years of experience . You will design,train and deploy vision and analytics models that run on real factory floors and enterprise systems,from camera capture to the final pass,reject or alert decision
  • Working experience with OpenCV and at least one deep learning framework (TensorFlow or PyTorch).

Job Description

About Techasoft and the work you will join

Techasoft is a Bangalore-based software company, founded in 2016, with a growing focus on enterprise AI and computer vision work. You will join the team that builds systems like these three:

  • Bad biscuit detection and rejection : deep learning plus OpenCV contour detection on high-speed industrial cameras, with automatic rejection of defective units. It reached 94% defect detection accuracy.
  • Mahindra vehicle pre-delivery inspection : multi-camera checks at inspection stations, matched to each vehicles variant and Bill of Materials through VIN and MES APIs, with edge AI inference, automatic pass or hold decisions and a timestamped audit record.
  • AI employee monitoring and compliance : behavioural analytics on Kafka and Spark, with TensorFlow models for baselines, anomaly detection and risk scoring, and a React dashboard for human review.

Job: AI and Computer Vision Engineer

Bangalore | Full Time | Starts immediately | 2+ years of experience

You will design, train and deploy vision and analytics models that run on real factory floors and enterprise systems, from camera capture to the final pass, reject or alert decision.

Responsibilities

  • Build and train deep learning models for defect detection, object detection and classification on industrial camera images.
  • Write OpenCV pipelines for preprocessing, contour detection and measurement on conveyor and inspection-station feeds.
  • Deploy models for edge inference and keep them updated from a central place.
  • Connect vision output to plant systems such as MES, VIN and BoM APIs, and to rejection mechanisms like air jets or robotic arms.
  • Build anomaly detection and risk scoring models on event streams, with clear confidence scores for human reviewers.
  • Produce dashboards, audit records and image evidence that clients can trust in audits.
  • Track accuracy, false rejects and missed defects, and retrain when production conditions change.
  • Write clean, documented Python code and take part in design and code reviews.

Requirements

  • 2+ years of hands-on Python development.
  • Working experience with OpenCV and at least one deep learning framework (TensorFlow or PyTorch).
  • Practical knowledge of CNN-based classification and object detection, and of dataset labelling and augmentation.
  • Understanding of model evaluation: precision, recall and accuracy in a production setting.
  • Experience with REST APIs and databases (PostgreSQL, MySQL or MongoDB).
  • Familiarity with Git, Docker and Linux.
  • Clear written and spoken English, and the ability to explain results to non-technical clients.

Good to have

  • Edge deployment experience (NVIDIA Jetson, ONNX or TensorRT).
  • Streaming and data tools such as Kafka, Spark or Redis.
  • React for reviewer dashboards.
  • AWS or Azure cloud deployment.
  • Time series or behavioural anomaly detection experience.
  • Exposure to industrial cameras, lighting setup or manufacturing quality systems.

What you get

  • Work on enterprise AI projects with manufacturing and large corporate clients.
  • Direct exposure to end-to-end delivery, from site visit to go-live.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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