Hi All,

Greetings from Valuelabs!!!

? We are hiring Machine Learning Architect/Lead

We are looking for an experienced Machine Learning Engineer with 10+ years of experience in Machine Learning, Deep Learning, and Computer Vision. Please find the detailed JD below and interested candidates please share your resume to mail id mentioned

JD

Senior Machine Learning Engineer – Computer Vision Experience 10+ years of industry experience in Machine Learning, Deep Learning, and Computer Vision with a proven track record of designing, building, and deploying production-grade AI solutions at scale.

Key Responsibilities - Design, develop, train, evaluate, and deploy production-grade machine learning and deep learning models for computer vision applications.

- Build end-to-end machine learning pipelines covering data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, monitoring, and continuous improvement.
- Train deep neural networks from scratch on large-scale image datasets and optimize model architectures for accuracy, latency, scalability, and robustness.
- Develop computer vision solutions for image classification, object detection, segmentation, localization, image similarity, and feature extraction.
- Own the complete machine learning lifecycle, including experiment design, hyperparameter optimization, model versioning, model registry, reproducible training pipelines, and model performance monitoring.
- Design and optimize distributed training pipelines utilizing multiple GPUs and efficiently process large-scale datasets.
- Evaluate model performance using statistical methods, rigorous experimentation, and business-centric success metrics.
- Apply model explainability techniques to validate, interpret, and communicate model predictions.
- Build scalable training and inference pipelines using AWS SageMaker and other cloud-native services.
- Collaborate closely with Product Managers, Data Scientists, Machine Learning Engineers, Software Engineers, Data Engineers, QA teams, domain experts,



and business stakeholders to deliver production-ready AI solutions.
- Drive continuous model improvements through hypothesis-driven experimentation, error analysis, performance optimization, and data-driven decision making.
- Lead and mentor Machine Learning Engineers, Data Scientists, and Software Engineers. Provide technical direction, establish engineering best practices, conduct architecture and code reviews, and drive execution of large-scale machine learning initiatives.

Required Technical Skills Machine

Learning - Strong understanding of supervised and unsupervised learning algorithms.
- Hands-on experience with regression, classification, clustering, ensemble learning, decision trees, random forests, and gradient boosting algorithms such as XGBoost, LightGBM, and CatBoost.
- Strong foundation in probability, statistics, hypothesis testing, experimental design, and statistical inference.
- Experience with feature engineering, model evaluation, cross-validation, bias-variance analysis, model calibration, and hyperparameter optimization. Deep Learning & Computer Vision - Strong expertise in TensorFlow (mandatory).
- Extensive experience training deep learning models from scratch on large-scale image datasets.
- Strong understanding of convolutional neural networks and modern computer vision architectures.
- Experience with image classification, object detection, semantic segmentation, instance segmentation, localization, embeddings, feature extraction, and image similarity.
- Experience designing custom neural network architectures, optimization techniques, loss functions, and distributed deep learning workflows.

Production Machine





Learning (Mandatory) - Proven experience designing, deploying, and operating production machine learning systems.
- Experience building scalable machine learning training and inference pipelines.
- Experience with model registry, experiment tracking, model versioning, CI/CD for machine learning, and model monitoring.
- Experience designing data ingestion pipelines and managing large-scale datasets.
- Hands-on experience with distributed training and multi-GPU environments.
- Strong understanding of machine learning system scalability, performance optimization, and production reliability. Programming & Software Engineering - Expert-level Python programming skills with experience building production-quality machine learning applications, reusable libraries, and scalable data processing pipelines.
- Solid understanding of software engineering principles, object-oriented design, design patterns, testing, debugging, performance optimization, and version control.
- Experience writing modular, maintainable, and production-quality code.
- Strong SQL and data analysis skills. Cloud & Infrastructure - Hands-on experience with AWS SageMaker.
- Experience deploying machine learning workloads on AWS.
- Familiarity with cloud-native machine learning infrastructure and scalable training environments.

Preferred Qualifications - Experience in automobile insurance, collision repair, automotive AI, or related computer vision domains.

- Experience building enterprise-scale machine learning products serving production customers.
- Exposure to MLOps platforms, distributed computing, and large-scale machine learning infrastructure.

? Location: Hyderabad (Hybrid/

Remote)

⏳ Notice period: Immediate to 15 days p referred

If you are interested, please share your updated resume or tag suitable candidates in the comments.

#Hiring #MachineLearning #DeepLearning #ComputerVision #TensorFlow #ArtificialIntelligence #MLOps #AWSSageMaker #Python #HyderabadJobs #AIJobs

📌 Senior Machine Learning Engineer (Hyderabad)
🏢 ValueLabs
📍 Hyderabad