Junior ML Engineer (Computer Vision)

Maximl Labs Pvt. Ltd.; Bangalore Rural; Sur place; INR 1 500 000 - 2 500 000; Plein temps

Résumé du poste

Maximl Labs Pvt. Ltd. in Bangalore seeks a computer vision engineer to build and deploy production CV systems. You will optimize models for cloud GPUs and edge devices, lead MLOps efforts, and collaborate with product engineering to deliver scalable CV features.

The role requires 1–2 years of hands-on experience with YOLO/TensorFlow/PyTorch, TensorRT, Triton, and cloud platforms. A strong bias for reproducibility and CI/CD is essential.

Qualifications

• 1–2 years of experience building, deploying and managing production CV systems on cloud infrastructure.
• Experience deploying computer vision models for object detection, VQA, image classification and OCR.
• Experience with model optimization for high performance/low-cost inference on cloud GPUs.
• Experience with YOLO, TensorFlow, PyTorch, TensorRT, Triton Server.
• Experience optimizing models for mobile/edge devices.

Responsabilités

• Stay updated on CV advances and evaluate new techniques.
• Develop proofs-of-concept and run A/B experiments.
• Compress, quantize, and accelerate models for cloud GPUs and edge devices.
• Provide technical leadership through code reviews and design reviews.
• Collaborate with product engineering to translate requirements into features.
• Define coding standards and documentation for CV projects.
• Evaluate architecture and compute infrastructure choices.
• Set up monitoring for model drift and retraining strategies.

Connaissances

CV systems

MLOps

Cloud computing

YOLO

TensorFlow

PyTorch

TensorRT

Edge inference

Outils

TensorRT

Triton Server

AWS

GCP

Azure

Description du poste

Bangalore North, India | Posted on 12/26/2025

Key Responsibilities

• Driveresearch & innovation Stay abreast of the latest academic andindustry advances in computer vision, like - object detection, segmentation,visual-language models, reasoning, OCR, video processing etc—evaluate andintegrate promising new techniques.
• Prototypeand validate new models Rapidly develop proof-of-concepts, runthorough A/B experiments, and establish robust evaluation benchmarks to de-risktechnology choices before production.
• Optimizefor production at scale Lead efforts to compress, quantize, andaccelerate models for cloud GPUs/TPUs and edge devices; integrate with CI/CD,automated testing, and containerized MLOps frameworks.
• Mentorand coach engineers Provide technical leadership through codereviews, design reviews, brown-bag talks, and best-practice guidelines; helpmid- and junior-level engineers grow their CV expertise and career.
• Collaboratecross-functionally Work closely with product engineering teams, solutiondelivery, customer success and end customers to translate business requirementsinto technical specs, ensure data quality and availability, and deliverfeatures that solve real customer safety-compliance problems.
• Defineand enforce coding standards Establish style guides, testing protocols,performance budgets, and documentation standards for CV projects; championreproducibility and clean, well-documented code.
• Leadtechnical architecture decisions Evaluate and select frameworks, libraries,annotation tools, and compute infrastructure; balance trade-offs betweenflexibility, performance, and cost.
• Monitorand improve model performance Set up monitoring dashboards and alerting formodel drift, accuracy regressions, and runtime failures; spearhead root-causeanalyses and continuous retraining strategies.

Requirements

• 1-2 years prior experience building,deploying and managing production-scale Computer Vision (CV) systems usingmodern deep learning models and MLOps tools and deployed on cloudinfrastructure (AWS/GCP/Azure).
• Has trained and deployed in production, computer vision models foruse-cases like object detection, visual question answering, imageclassification, visual attribute extraction, text detection & extraction /OCR etc.
• Practical experience working on model optimization forhigh-performance/low-cost inference for cloud GPUs.
• Prior experience with multiple of thefollowing: YOLO, TensorFlow, PyTorch, NVidia TensorRT, Triton Server etc
• Experience optimizing models formobile/edge devices.