Job Description
Job Title: Mid-level AI/ML Engineer
Experience: 2–4 years
Job Summary:
We are seeking a hands-on AI/ML Engineer to join our Research and Innovation
team, focused on building and deploying intelligent systems for real-world
environments. You will work on production-grade computer vision pipelines,
multimodal AI workflows, and data-driven analytics systems powering products like
retail monitoring, compliance tracking, and behavioral insights.
This role sits at the intersection of engineering and applied machine learning. You
will independently develop models and pipelines, contribute to system design, and
collaborate across backend, DevOps, and product teams to deliver scalable AI
solutions.
Key Responsibilities:
âDesign, build, and optimize computer vision pipelines for real-world
monitoring (e.g., object detection, tracking, activity recognition)
âDevelop and maintain ML models for tasks such as detection, classification,
clustering, and re-identification
âImplement data processing pipelines for images, video streams, and
structured monitoring data
âWork with model inference frameworks (ONNX, PyTorch, TensorRT) for
efficient deployment
âContribute to custom AI workflows, including rule engines, event detection
systems, and multimodal reasoning layers
âOptimize models and pipelines for performance constraints (low latency,
limited VRAM, edge deployment)
âCollaborate with backend teams to integrate AI outputs into APIs and
production systems
âParticipate in model evaluation, experimentation, and continuous
improvement cycles
âDebug and resolve issues across training, inference, and production
environments
âContribute to architecture discussions around AI pipelines, data flows, and
system design
Required Skills & Qualifications:
âBachelor’s degree in Computer Science, AI, Machine Learning, or related field
(or equivalent experience)
âStrong understanding of machine learning fundamentals and deep learning
concepts
âSolid experience with Python and PyTorch
âExperience with computer vision models (e.g., YOLO, ResNet, EfficientNet,
Transformers)
âUnderstanding of embeddings, similarity search, and clustering techniques
(e.g., UMAP, k-means, DBSCAN)
âFamiliarity with model deployment workflows (ONNX, inference optimization,
model serving)
âExperience working with image/video data pipelines
âStrong grasp of OOP, data structures, and system design basics
âWorking knowledge of SQL and data handling
âFamiliarity with REST APIs and backend integration
âExperience with Git and collaborative development workflows
Nice to Have
âExperience with object tracking (e.g., DeepSORT, ByteTrack)
âFamiliarity with edge AI or real-time inference systems
âExposure to multimodal AI (vision + language models)
âExperience with cloud platforms (AWS, Azure) and GPU-based workloads
âUnderstanding of CI/CD for ML pipelines
âExperience working in Agile/Scrum teams
âFamiliarity with Node.js pipelines for inference integration
What You’ll Work On
âReal-time monitoring systems analyzing camera feeds for operational insights
âPerson re-identification and behavioral tracking pipelines
âEvent detection engines powered by AI + rule-based systems
âModular AI pipelines adaptable across industries (retail, service, compliance)
âOptimization of models for deployment in constrained environments
