on cloud and edge devices.
Implement model compression, quantization, and deployment pipelines.
Deployment & Orchestration
Deploy Vision AI agents on
edge devices, cameras, and cloud-native platforms
.
Collaborate with Platform and AgentOps engineers to ensure reliability, scalability, and observability.
Integrate Vision AI systems with enterprise data streams and workflows.
Responsible AI & Quality
Ensure Vision AI agents adhere to
safety, fairness, and compliance
standards.
Build evaluation pipelines for accuracy, bias, and real-world robustness.
Document best practices and create reproducible workflows for enterprise customers.
SKILLS REQUIREMENTS
Technical Skills:
2-5 years of experience in
computer vision, ML engineering, or applied AI
.
Strong knowledge of
deep learning frameworks
(PyTorch, TensorFlow, OpenCV).
Experience with
object detection/recognition models
(YOLO, Faster R-CNN, DETR, SAM).
Familiarity with
multimodal AI
(vision + LLMs).
Hands-on experience with
cloud platforms (AWS, Azure, GCP)
and
edge AI deployments
.
Knowledge of
inference optimization
(ONNX, TensorRT, OpenVINO).
Proficiency in
Python
, with solid engineering practices (Git, CI/CD).
Professional Attributes:
Strong problem-solving skills and ability to translate business needs into AI solutions.
Collaboration mindset -- able to work across AI, platform, and product teams.
Curiosity for emerging
agentic AI frameworks
(LangGraph, CrewAI, MCP).
Passion for building
real-world AI systems that matter
.
CAREER GROWTH AND BENEFITS
1) Continuous Learning & Growth
Certifications and advanced training in
Vision AI, MLOps, and Agentic AI
.
Opportunity to work on
enterprise-grade Vision AI deployments
.
2) Recognition & Rewards
Performance-based incentives and recognition for impactful agentic solutions.
Career progression toward
AI Architect
or
Vision AI Product Lead
roles.
3) Work Benefits & Well-Being
Comprehensive health insurance and wellness support.
Additional allowances for project-based roles and