929 model jobs in Bengaluru, India.

... Life, CRED, IDFC, and LIC. About the Role We are hiring a Model Product Manager to own charters for Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and model evaluation pipelines. You will work closely with research and engineering teams to define roadmaps, run training and evaluation cycles, and ship models that ...

• Hybrid
• On-site

... https://jobeax.com/link/S3kBynSDsnH6JK7i Responsibilities:- Build and manage MLOps and LLMOps pipelines.- Deploy, host, and scale Deep Learning models, LLMs, and SLMs.- Manage model versioning, deployment, rollout, rollback, and retirement.- Host models on Databricks, Kubernetes, OpenShift, and GPU infrastructure.- Implement model governance, ...

• Hybrid

... building models, you will guide feature engineering strategies, experimentation approaches, validation standards, and production-readiness practices to ensure models are reliable, explainable, and maintainable in real-world environments. This role is ideal for someone who is equally comfortable developing models, operationalizing ...

... DBSCAN. Experience with feature engineering, feature selection, dimensionality reduction, hyperparameter optimization, cross-validation, model calibration, and model evaluation. Proficiency in Python, Pandas, NumPy, Scikit-learn, with experience using libraries such as XGBoost, LightGBM, CatBoost, and Statsmodels. Experience ...

Key Responsibilities:- Develop, train, and optimize production-grade computer vision models - object detection, instance segmentation, classification, and tracking.- Deploy and optimize models on embedded AI platforms and edge devices for low-latency, real time inference.- Build and integrate end-to-end CV pipelines into ...

... secrets handling, access controls, and release governance across CI/CD and runtime environments to improve security and audit readiness.Must-Have Skills :- MLOps & Model Lifecycle : MLOps, Model deployment and serving.- Cloud-Native Infrastructure & Orchestration : Containers, Kubernetes.- Delivery Automation & Release Engineering ...

... engineering, model evaluation, grounding, and retrieval strategies.- Implement vector search, embeddings, semantic search, and knowledge retrieval.- Deploy AI models and applications in scalable production environments.- Optimize model performance, latency, scalability, and infrastructure utilization.- Implement AI application ...

... and experimentation to https://jobeax.com/link/rH0yu1ler9U2ioyx Responsibilities : - Model Training & Fine-Tuning : Train and fine-tune deep learning and LLM models using domain-specific datasets.- Model Evaluation : Design benchmarks, evaluation frameworks, metrics, and error-analysis processes to measure model quality ...

... Analytics:- Guide teams in developing predictive models, classification models, recommendation systems, forecasting solutions, and other advanced analytical models.- Review model approaches, feature engineering, statistical techniques, and validation methodologies.- Ensure models are robust, scalable, explainable, and ...

... analysis, factor analysis Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms Test/train the model, Improve Model accuracy, Monitor model performance Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation, transformation), ...

• Full-time

... preparation, transformation, feature engineering, and analysis. - Develop and optimise machine learning models based on business and product requirements. - Evaluate model performance using appropriate metrics, validation techniques, and experimentation frameworks. - Build production-ready ML pipelines and integrate models into ...

... frameworks and metrics for AI/ML/GenAI solutions. - Review model outputs, prompts, retrieval quality, accuracy, relevance, and reliability. - Maintain evidence of model and prompt evaluation throughout the development lifecycle. - Identify and mitigate hallucinations, bias, inconsistent outputs, and other modelrelated risks. ...

... data preprocessing, feature engineering, and exploratory data analysis (EDA) to support model development. - Build and deploy end-to-end ML pipelines, including model training, evaluation, and serving in production environments. - Monitor and maintain deployed models to ensure robustness, scalability, and performance over ...

... Responsibilities :- Design and perform BIM Modelling for specific design discipline under the supervision / direction of BIM Coordinator / BIM Manager. Ensure models / drawings accuracy based on BIM standards and BIM project workflow criteria / checklist. Clean up and synchronize models/drawings daily to the cloud collaboration ...

... https://jobeax.com/link/ao2QBbKt4vW7ruJ1 Technical Requirements : - 4 to 9 years as an AI/ML engineer with production systems behind you.- Depth across the modern AI stack : LLMs, speech models, vector retrieval, model serving.- Strong software engineering skills.- Fluency in Python and the production ML ecosystem. (ref:hirist.tech)

• On-site
• Full-time

... Indian Institute of Science (IISc). The company is building advanced AI for the planning and operations of critical networks. Its core technology is a World Model for critical networks — frontier AI, not another LLM wrapper. The founding team previously built and scaled a deep-tech company in the private 5G and cellular ...

... problems and enhance system capabilities.3. Data Processing :- Oversee data collection, preprocessing, and feature engineering to ensure high-quality input for AI models.4. Model Training and Evaluation :- Train and fine-tune machine learning models using large datasets and rigorously evaluate model performance using appropriate ...

... develop, and implement AI/ML-based solutions using Python.- Build and fine-tune models using TensorFlow, PyTorch, or similar frameworks.- Apply Large Language Models (LLMs) to build and optimize NLP-based services.- Preprocess large datasets, engineer features, and evaluate model performance.- Collaborate with senior engineers ...

• Remote
• Hybrid
• Full-time

... models, fine-tuned LLMs, and rule/ML hybrid approaches. Build and maintain training and evaluation datasets, labeling workflows, and benchmark suites. Track model performance through precision/recall, error analysis, drift, and adversarial robustness . Serve models in production under strict latency requirements, working ...

• Hybrid

... https://jobeax.com/link/XIA7wD9gSNU9qtiD Responsibilities :- Pipeline Ownership: Design and manage complex, multi-stage RAG pipelines ensuring low latency and high relevance.- Model Optimization: Lead fine-tuning initiatives (PEFT/LoRA) for open-source models to improve domain-specific task performance.- Advanced Evaluation: Develop automated ...