3,146 model jobs in India.

... 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 ...

• Full-time

Rs 25 - 30 lakhs p.a.

... architectures using frameworks such as TensorFlow, PyTorch, or equivalent technologies. - Perform exploratory data analysis, feature engineering, statistical analysis, model selection, and hyperparameter optimization. - Evaluate model performance using appropriate statistical and business metrics and continuously improve model accuracy, ...

• Remote

... machine learning pipelines. You will work closely with data scientists, infrastructure engineers, and product stakeholders to bridge the gap between experimental models and robust, scalable deployments. By leveraging Kubeflow for orchestration and Langfuse for LLM observability, you will ensure that our AI systems are not only ...

• Remote

... machine learning pipelines. You will work closely with data scientists, infrastructure engineers, and product stakeholders to bridge the gap between experimental models and robust, scalable deployments. By leveraging Kubeflow for orchestration and Langfuse for LLM observability, you will ensure that our AI systems are not only ...

• Hybrid

... Establish and manage operational standards for the AI lifecycle, including model fine-tuning, prompt versioning, semantic caching, rate limiting, and dynamic model routing to optimize for latency, cost (token economy), and performance. Implement CI/CD pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop ...

• Hybrid

... Establish and manage operational standards for the AI lifecycle, including model fine-tuning, prompt versioning, semantic caching, rate limiting, and dynamic model routing to optimize for latency, cost (token economy), and performance. Implement CI/CD pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop ...

• Hybrid

... Establish and manage operational standards for the AI lifecycle, including model fine-tuning, prompt versioning, semantic caching, rate limiting, and dynamic model routing to optimize for latency, cost (token economy), and performance. Implement CI/CD pipelines for AI/ML workloads.- Model Evaluation & Observability : Develop ...

... Responsibilities :- Build and productionize ML and AI solutions for wealth management and investment use cases, including portfolio optimization, asset allocation, risk modeling, forecasting, investor personalization/recommendations, financial NLP, RAG, and AI agents.- Develop scalable ML/AI pipelines for training, evaluation, deployment, ...

Job Specification: Create exam-oriented content for UPSC and State PCS (Prelims + Mains) including MCQs with explanations, Mains questions, and model answers as per latest exam pattern. Job Purpose: Content creation for UPSC and State PCS (Prelims + Mains) as per latest syllabus and exam pattern. Create MCQs with detailed ...

• Contract

Build What Matters at Model N :At Model N, we help life sciences companies solve complex revenue challenges so they can operate smarter and bring important innovations to market faster. If you are energized by platform architecture and developer experience, the opportunity to lead a team of product managers through a major ...

• Remote

... documents. The Manager, Model Validation is responsible for model validation focusing on Loss/reserve/recovery/ forecast to Customer facing credit risk/Fraud risk models (Account acquisition and Account management) , and other models and ensure they are meeting the related Model Risk Management policies, standards, procedures ...

... 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), ...

... pipelines using AWS services. Design and implement scalable, secure, and resilient MLOps architecture across cloud and on-prem environments Define best practices for model lifecycle management, including versioning, deployment, monitoring, and governance Lead the selection and integration of tools for CI/CD, model registry, feature ...

• 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 ...

... validation through production deployment, monitoring, and retirement. Define architectural patterns and best practices for model versioning, reproducibility, model registries, automated testing, deployment pipelines, A/B testing, and model retraining workflows. Ensure solutions align with enterprise model governance standards, ...

... and perform data analysis with Python and SQL Create workflows for model development and apply feature engineering methods Use Azure AI Search to make data and models easier to consume for business needs Coordinate with developers and project managers using GitLab and Jira Refine data pipelines and tune model performance ...

... 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. ...

... Agentic AI technologies. Required Technical Skills Strong proficiency in Python Machine Learning fundamentals Natural Language Processing (NLP) Generative AI and Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Embeddings and semantic search Model evaluation and validation techniques

... 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 ...