Position: MLOps Engineer

Location: Bengaluru/Salem
No of Position: 2

Experience: 4-6 Yrs

Core Competencies:

Valuable Understanding of Machine Learning project lifecycle Experience in architecting and implementing high-performance RESTful micro services (API development for ML Models) Familiarity with MLOps and experience with scaling and deploying Machine Learning models Experience with cloud-based machine learning platforms (e.g., AWS SageMaker, Azure ML Service, Databricks). Experience with MLOps tools ( MLflow, Tecton, Pinecone, Feature Stores)Experience with AIOps or related fields like IT automation or incident management.

Experience building and operating large-scale distributed systems using Amazon Web Services/Azure (S3, Kinesis, Cloud Formation, EKS, AWS Security and Networking). Experience with using OpenAI LLMs.Core Competencies: Machine Learning, Artificial Intelligence, Predictive Analytics, Prescriptive Analytics, Model Training, Algorithm Implementation, Data Science, Deep Learning, Natural Language Processing, Computer Vision Tools Technologies: TensorFlow, PyTorch, scikit-learn, Keras, Apache Spark MLlib, H2O.ai,



AWS SageMaker, Azure Machine Learning, Google AI Platform, Jupyter Notebooks, Data Management: Data Preprocessing, Feature Engineering, Data Transformation, Data Wrangling, Data Visualization, ETL Processes

Programming Languages: Python, R, SQL, Java, Scala, C++ Deployment Integration: Model Deployment, RESTful APIs, Docker, Kubernetes, CI/CD Pipelines, Cloud Services Integration Methodologies: Supervised Learning, Unsupervised Learning, Reinforcement Learning, Ensemble Methods, Transfer Learning, Hyperparameter Tuning Optimization Performance: Model Optimization, A/B Testing, Scalability, Performance Tuning, Distributed Computing Soft Skills: Problem Solving, Critical Thinking, Collaboration, Communication, Continuous Learning

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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