Senior AI/ML Engineer

INVIDI Technologies Corporation

Sr. AI/ML Engineer developing AI systems across the machine learning lifecycle for media applications.

Posted 7/2/2026full-timeChennai • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production machine learning systems, with a strong focus on computer vision, model optimization for cloud and edge environments, and the development of scalable ML pipelines. Proficient in Python and experienced with AWS services for implementing machine learning solutions.

Highest-signal resume keywords

Computer Vision ExpertiseDeep Learning Frameworks (PyTorch, TensorFlow)Model Optimization for Cloud and EdgeAWS Cloud Services (SageMaker, Lambda, S3)Scalable ML Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning SystemsObject DetectionImage UnderstandingDeep Learning Model TrainingModel EvaluationImage EmbeddingSimilarity RetrievalPython DevelopmentCI/CD PipelinesData Collection Strategies

Soft Skills

CollaborationProblem-SolvingInnovation

Tools & Technologies

AWS SageMakerAWS LambdaAWS S3PyTorchTensorFlow

Industry Keywords

Production AI ModelsVisual SearchMobile ML PerformanceAutomated Evaluation WorkflowsBenchmarking and Evaluation Pipelines

Tech Stack

Tools & technologies

AndroidAWSCloudiOSPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Build and Improve Production AI Models
Design, train, fine-tune, and deploy state-of-the-art computer vision models for object detection, image understanding, and visual search
Improve model robustness across challenging real-world scenarios including varying lighting conditions, perspective changes, motion blur, occlusion, compression artifacts, and partial captures
Continuously evaluate and iterate on models using production feedback and newly collected data
Optimize AI for Mobile and Cloud
Optimize inference performance for both edge and cloud deployments, balancing accuracy, latency, memory usage, and operational cost
Improve mobile ML performance across iOS and Android while accounting for device constraints such as thermal throttling, battery usage, and hardware acceleration
Build scalable cloud inference services capable of supporting high-volume production workloads
Build a World-Class ML Platform
Design reproducible training pipelines, model versioning strategies, and automated evaluation workflows
Establish quality gates and validation processes to ensure models meet production standards before deployment
Improve CI/CD pipelines, artifact management, and promotion workflows across development, staging, and production environments
Own Data Quality and Evaluation
Develop data collection strategies that improve model performance and generalization
Create synthetic and augmented datasets to increase robustness across diverse operating conditions
Build automated benchmarking and evaluation pipelines with measurable performance metrics and regression testing
Improve Visual Search and Retrieval
Design and optimize image embedding and similarity search pipelines
Improve semantic matching, reranking, and retrieval quality for image-based search experiences
Evaluate new architectures and techniques that enhance accuracy and user experience
Collaborate Across Engineering Teams
Work closely with mobile and backend engineers to integrate AI models into production applications
Debug end-to-end ML systems, from training pipelines and inference services to client-side image preprocessing and post-processing
Contribute to technical architecture decisions and establish best practices for scalable AI development
Drive Innovation
Evaluate emerging AI technologies and identify opportunities to improve existing capabilities
Prototype new features in computer vision, multimodal AI, recommendation systems, and conversational AI
Help shape the long-term AI strategy and technical roadmap

Requirements

What you’ll need

5+ years of experience building and deploying production machine learning systems
Strong expertise in computer vision, including object detection, image understanding, and visual embeddings
Experience training, fine-tuning, evaluating, and deploying deep learning models using real-world datasets
Hands-on experience with modern deep learning frameworks such as PyTorch or TensorFlow
Experience optimizing models for both cloud and edge/mobile deployment
Strong understanding of vector search, similarity retrieval, and embedding-based systems
Experience building scalable ML pipelines, model evaluation frameworks, and production inference services
Excellent Python development skills and the ability to work across multiple parts of the technology stack
Strong experience with AWS cloud services, including designing and deploying ML solutions using SageMaker, Lambda, S3 and related services

Benefits

Comp & perks

Health insurance
Flexible work arrangements
Professional development opportunities