AI/ML Engineer - Computer Vision - CodeCraft Technologies

Location: Bangalore

No. of Positions: 01

Experience: 2-4yrs

Role Description

We are looking for a Machine Learning & Computer Vision Engineer to design, develop, and deploy end-to-end AI solutions. The role involves building deep learning and classical ML models, creating scalable ML pipelines, and delivering production-ready systems on AWS. You will work on object detection, segmentation, OCR, tracking, and other vision tasks using modern frameworks, while applying strong MLOps practices for automation, monitoring, and continuous improvement. Collaboration with Data Engineering, Product, and Backend teams is essential to integrate AI capabilities into enterprise applications and ensure high performance and reliability.

Key Responsibilities:

• Design and develop

  machine learning and computer vision models

  , including deep learning and classical ML solutions.
• Implement architectures for

  object detection, segmentation, tracking, OCR, anomaly detection

  , and other vision tasks.
• Build

  end-to-end ML pipelines

  encompassing data acquisition, preprocessing, feature engineering, model training, validation, optimization, and production deployment.
• Leverage

  classical machine learning algorithms

  such as

  Random Forests, Gradient Boosting (XGBoost / LightGBM / CatBoost), SVM, Linear/Logistic Regression, KNN, PCA, Clustering

  , etc., when appropriate for tabular or image-feature-based problems.
• Conduct

  model experimentation

  and performance evaluation using relevant metrics and statistical techniques.
• Deploy ML models to production using

  AWS services

  such as

  SageMaker, Lambda, S3, EC2, ECR, Step Functions, API Gateway, DynamoDB, CloudWatch

  , and

  EKS

  .
• Build and manage scalable

  real-time or batch inference

  systems.
• Collaborate with Data Engineering, Product, and Backend teams to integrate AI components into enterprise solutions.
• Apply

  MLOps practices

  including CI/CD, model versioning, automated retraining, monitoring, and observability.
• Work with large-scale image/video/audio datasets and manage annotation and data processing workflows.

Required Qualifications

• 2-4 years

  of hands-on experience in

  machine learning

  , including both

  classical ML and deep learning

  .
• Strong experience with deep learning frameworks:

  PyTorch, TensorFlow, Keras

  .
• Solid grounding in

  classical ML

  , feature engineering, model selection, hyperparameter tuning, and evaluation techniques.
• Expertise in

  computer vision frameworks

  such as

  OpenCV, Detectron2, YOLO, Mask R-CNN, UNet, ViT, OpenVINO

  , etc.
• Strong ability to write production-grade code in

  Python

  , including NumPy, Pandas, Scikit-learn, and model-serving frameworks (FastAPI / Flask).
• Proven experience deploying solutions on the

  AWS cloud ecosystem

  .
• Experience with

  Docker

  ,

  Kubernetes

  , and distributed or accelerated training environments.
• Hands-on experience with

  REST APIs

  , microservices architecture, and real-time inference.
• Familiarity with

  MLOps tools and practices

  such as MLflow, Kubeflow, Airflow, or SageMaker Pipelines.
• Strong understanding of software engineering fundamentals: Git, testing, system performance, and release management.

Preferred Skills

• Exposure to

  Generative AI / multimodal models / video analytics

  .
• Experience deploying on

  edge devices

  (NVIDIA Jetson, TensorRT, ONNX Runtime).
• Experience with data labeling tools and annotation pipelines.
• Familiarity with

  CI/CD

  frameworks (GitLab, GitHub Actions, AWS CodePipeline).
• Experience with Agile/Scrum processes.