AI / ML Engineer

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:
●Design, build, and optimize computer vision pipelines for real-world
monitoring (e.g., object detection, tracking, activity recognition)
●Develop and maintain ML models for tasks such as detection, classification,
clustering, and re-identification
●Implement data processing pipelines for images, video streams, and
structured monitoring data
●Work with model inference frameworks (ONNX, PyTorch, TensorRT) for
efficient deployment
●Contribute to custom AI workflows, including rule engines, event detection
systems, and multimodal reasoning layers
●Optimize models and pipelines for performance constraints (low latency,
limited VRAM, edge deployment)
●Collaborate with backend teams to integrate AI outputs into APIs and
production systems
●Participate in model evaluation, experimentation, and continuous
improvement cycles
●Debug and resolve issues across training, inference, and production
environments
●Contribute to architecture discussions around AI pipelines, data flows, and
system design

Required Skills & Qualifications:
●Bachelor’s degree in Computer Science, AI, Machine Learning, or related field
(or equivalent experience)
●Strong understanding of machine learning fundamentals and deep learning
concepts
●Solid experience with Python and PyTorch
●Experience with computer vision models (e.g., YOLO, ResNet, EfficientNet,
Transformers)
●Understanding of embeddings, similarity search, and clustering techniques
(e.g., UMAP, k-means, DBSCAN)
●Familiarity with model deployment workflows (ONNX, inference optimization,
model serving)
●Experience working with image/video data pipelines
●Strong grasp of OOP, data structures, and system design basics
●Working knowledge of SQL and data handling
●Familiarity with REST APIs and backend integration
●Experience with Git and collaborative development workflows
Nice to Have
●Experience with object tracking (e.g., DeepSORT, ByteTrack)
●Familiarity with edge AI or real-time inference systems
●Exposure to multimodal AI (vision + language models)
●Experience with cloud platforms (AWS, Azure) and GPU-based workloads
●Understanding of CI/CD for ML pipelines
●Experience working in Agile/Scrum teams
●Familiarity with Node.js pipelines for inference integration

What You’ll Work On
●Real-time monitoring systems analyzing camera feeds for operational insights
●Person re-identification and behavioral tracking pipelines
●Event detection engines powered by AI + rule-based systems
●Modular AI pipelines adaptable across industries (retail, service, compliance)
●Optimization of models for deployment in constrained environments