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Urgent! Charter Global - Senior AI/ML Engineer - AWS SageMaker Job Opening In Hyderabad – Now Hiring Charter Global Technologies

Charter Global Senior AI/ML Engineer AWS SageMaker



Job description

<p><p><b>Description :</b><br/><br/>Job Summary :<br/><br/>We are looking for a results-driven Senior AI/ML Engineer to lead the development and deployment of scalable machine learning models and intelligent systems.<br/><br/>You will be at the forefront of building AI solutions that solve high-value business problems, with full ownership from data preparation to model monitoring.<br/><br/>This is a key role in a hands-on, production-grade AI/ML team, working with state-of-the-art tooling and infrastructure.<br/><br/>Key Responsibilities :<br/><br/>- Design and implement robust, end-to-end ML models and AI pipelines to solve real-world business challenges.<br/><br/>- Build and maintain scalable data pipelines for structured and unstructured datasets including data extraction, cleansing, feature engineering, and labeling.<br/><br/>- Train and tune ML models using modern frameworks such as TensorFlow, PyTorch, and scikit-learn.<br/><br/>- Deploy models to production using MLOps tools like MLflow, Kubeflow, or Amazon SageMaker.<br/><br/>- Collaborate with Product, Engineering, and Data Science teams to embed ML into customer-facing solutions.<br/><br/>- Monitor and optimise models for performance, reliability, and drift detection in live environments.<br/><br/>- Conduct R&D on cutting-edge techniques in LLMs, NLP, and computer vision, and apply them to production use cases.<br/><br/>- Build internal dashboards, logs, and traceability features to ensure robust model governance.<br/><br/>- Write clean, reusable code and maintain thorough documentation of solutions and processes.<br/><br/><b>Required Skills & Qualifications :</b><br/><br/>- 8+ years of experience in machine learning, AI engineering, or applied data science roles.<br/><br/>- Deep fluency in Python and core ML libraries: NumPy, Pandas, scikit-learn, TensorFlow, PyTorch.<br/><br/>- Strong knowledge of ML algorithms, statistical modeling, and deep learning architectures (CNNs, RNNs, Transformers).<br/><br/>- Experience with cloud platforms such as AWS, Azure, or GCP for training and deploying models.<br/><br/>- Proficiency with Docker, Kubernetes, and DevOps tools for ML deployment.<br/><br/>- Hands-on experience with MLOps frameworks like MLflow, Kubeflow, or SageMaker.<br/><br/>- Familiarity with CI/CD pipelines, model registries, and version control best practices.<br/><br/>- Ability to work with large-scale, multimodal datasets (text, time series, images, etc.<br/><br/>- Strong analytical, problem-solving, and collaboration skills.<br/><br/><b>Preferred Qualifications :</b><br/><br/>- Masters degree in computer science, AI, Data Science, or a related field.<br/><br/>- Experience building applications using LLMs (e.g , GPT, BERT) or working on NLP and Computer Vision problems.<br/><br/>- Familiarity with Big Data tools such as Spark, Kafka, Databricks.<br/><br/>- Contributions to open-source ML/AI projects or peer-reviewed publications.<br/><br/>- Awareness of AI ethics, data privacy regulations, and responsible AI deployment practices.</p><br/></p> (ref:hirist.tech)


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