MLOps Lead/Architect

Experience: 10+ Years

Location: Bellandur, Bangalore/Chennai

Shift: 1:30 PM 10:30 PM

Work Mode: Monday - WFH and remaining( 4days - work from office)

Mandatory Skill: Python, MLOps, Azure Services, Computer Vision

Role Overview

We are looking for an experienced Lead Computer Vision Engineer with strong hands-on expertise in Python, deep learning, and computer vision technologies. The candidate will lead the development, optimization, and deployment of scalable AI/ML solutions across cloud and edge environments.

The role involves managing the complete computer vision engineering lifecycle, from problem definition and data preparation to model development, training, deployment, production monitoring, and continuous improvement.

Experience in industrial computer vision, video analytics, Oil & Gas, Energy, Manufacturing, or Industrial IoT will be an added advantage.

Key Responsibilities

- Design, develop, optimize, and deploy computer vision and deep learning models for real-world business applications.
- Lead the complete ML lifecycle, including data processing, feature engineering, model training, validation, deployment, and monitoring.
- Develop and implement object detection solutions using YOLO or equivalent frameworks.
- Build computer vision applications using Python, OpenCV, PyTorch, and TensorFlow.
- Deploy and scale AI/ML workloads across cloud and edge computing environments.
- Implement MLOps practices for model versioning, deployment automation, monitoring, and continuous improvement.
- Design scalable AI solutions while ensuring performance, reliability, security, and responsible AI practices.
- Collaborate with cross-functional teams and stakeholders to translate business requirements into effective AI solutions.
- Provide technical leadership, mentor engineers, and drive best practices across AI/ML development.

Required Technical Skills 1. Programming & Computer Vision

- Strong proficiency in Python.




- Hands-on experience with OpenCV and computer vision algorithms.
- Expertise in deep learning frameworks such as PyTorch or TensorFlow.
- Experience with YOLO or equivalent object detection frameworks.

2. AI & Machine Learning

- Strong understanding of Machine Learning, Deep Learning, NLP, and Generative AI.
- Knowledge of Large Language Models (LLMs), Agentic AI, and modern AI architectures.
- Experience in model optimization, data processing, and feature engineering.

3. MLOps & Deployment

- Strong understanding of MLOps and production ML lifecycle management.
- Experience with model deployment, monitoring, versioning, and CI/CD pipelines.
- Knowledge of MLflow, Kubeflow, Docker, Kubernetes, GitHub Actions, or Azure DevOps.

4. Cloud & Data Technologies

- Experience with Microsoft Azure AI Services, AWS SageMaker, or Google Vertex AI.
- Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Weaviate.
- Familiarity with Apache Spark, Databricks, data lakes, and big data platforms.

5. AI Architecture & Governance

- Understanding of AI solution architecture, responsible AI, and AI governance.
- Ability to design scalable, secure, and production-ready AI/ML solutions.

Required Experience
- 10+ years of experience in software engineering, AI/ML, or computer vision.
- Strong hands-on experience developing and deploying computer vision models.
- Proven track record of taking computer vision solutions from Proof of Concept (PoC) to production.
- Strong Python programming and deep learning expertise.
- Experience deploying AI/ML solutions on cloud and/or edge platforms.
- Experience leading technical teams or working as a technical lead.

Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- PhD in AI/ML is an added advantage.

Preferred Certifications
- Microsoft Azure AI Engineer Associate or Azure AI Architect certifications.
- AWS Machine Learning Specialty.
- Google Qualified Machine Learning Engineer.
- Databricks AI/ML certifications.

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