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Role - AI ML Developer
Experience - 5 to 12 years
Joining Location - PAN INDIA
Interview location - Bengaluru , Chennai , Hyderabad, Kolkata, Pune
Job description
· Strong knowledge of AI methodologies, including generative models, machine learning (ML), reinforcement learning, and natural language processing (NLP).
· Design, implement, and optimize generative AI architectures and models.
· Build Agentic AI solutions using LLMs, including tool/function calling, Model Context Protocol (MCP), memory, workflows, and orchestration.
· Collaborate with data scientists and analysts to collect, preprocess, and manage large datasets, ensuring data quality and integrity for model training.
· Collaborate with cross-functional teams to integrate AI models into production environments, ensuring seamless deployment and operational efficiency.
· Experience of cloud-based platforms (e.g., AWS, Azure, GCP) to develop and deploy scalable AI solutions, ensuring high availability and performance.
· Strong hands-on experience in end-to-end AI/ML engineering, including data preprocessing, feature engineering, model training, evaluation, and optimization for production use cases.
· Proficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).
HR
,Kaushik
,8610525163
.Job ID: 150936519
Skills:
Big Data Technologies, Tableau, Tensorflow, Numpy, Pytorch, Docker, Microsoft Azure, Python, Matplotlib, Hadoop, Power Bi, Machine Learning Algorithms, Sql, Deep Learning, Pandas, Spark, Seaborn, Kubernetes, Computer Vision, MLflow, data visualization tools, data engineering concepts, MLOps tools, ETL pipelines, Scikit-learn, cloud platforms, Generative AI technologies
Skills:
model selection , Python, Neural Networks, Clustering, 5G NR Core stack, RAG systems, CNNs, Supervised Classification, LangGraph, Time-Series Forecasting, Data pipelines, CrewAI, LSTMs, TFT, Root Cause Analysis, n8n, AI-native 6G architectures, Regression, GNNs, Transformers, Deep Reinforcement Learning, Knowledge Graphs, Model evaluation, Unsupervised Anomaly Detection
Skills:
Machine Learning, Python Programming, Artificial Intelligence, Kubernetes and Docker, REST API design
Skills:
data engineering , Docker, Data Cleaning, Rest Apis, AWS, Python, Azure, Cloud Infrastructure, Gcp, ETL pipelines, LLM-based systems, semantic search architecture, vector databases, embeddings, large-scale processing
Skills:
Scripting, Golang, microservice architecture, Numpy, Pandas, Scikit, Kubernetes, Python, AWS, GenAI Prompt Engineering, DevOps practices, cloud-native applications, Jupyter notebooks
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