| AI Ml Engineer, Austin, TX at Austin, Texas, USA |
| Email: [email protected] |
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From: Gaurav Nain, sibitalent.com [email protected] Reply to: [email protected] Job Title - Artificial Intelligence/Machine Learning Engineer II Location - Austin, TX HYBRID - 2 Days Office - must be within 1 hour Drive - GLIDER ASSESSMENT DUE TODAY OR ASAP Job Description: We are seeking a talented and innovative AI / Machine Learning Engineer to join our team. As part of the AI Technical Team, you will design, build, and deploy advanced machine learning models and AI solutions to solve real-world problems. You will work with large datasets, AI/ML frameworks, and cross-functional teams to deliver impactful results that align with our business goals. If you are passionate about machine learning, artificial intelligence, and creating high-performance models, wed love to hear from you. Key Responsibilities Experience should fall between 4-7 years. Model Development and Design: Develop, test, and optimize machine learning models for classification, regression, clustering, or recommendation tasks. Data Preparation: work alongside the Enterprise Data Management Team to collect, clean, preprocess, and analyze large datasets to create high-quality training datasets. Algorithm Implementation: Implement machine learning algorithms and neural networks using frameworks like TensorFlow, PyTorch, and scikit-learn. Deployment and Integration: Deploy trained models into production environments using APIs, containers (e.g., Docker), or cloud services (AWS, GCP, or Azure). Performance Monitoring: Monitor model performance, detect drift, and implement improvements or retraining strategies to ensure models remain accurate over time. Collaboration: Work closely with our data management team, applications team, enterprise architects, and product managers to align solutions with business needs. Documentation: Create thorough documentation for models, processes, and experiments to ensure reproducibility and scalability. MLOps Practices: Develop automated pipelines for continuous integration, delivery, and model retraining (CI/CD). Ethics and Compliance: Ensure AI models comply with industry regulations, address biases, and adhere to ethical standards. Minimum Yrs of Experience, Skills, and Qualifications Required Skills & Qualifications Education: Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Engineering, or a related field. Programming Skills: Proficiency in Python, R, or similar programming languages. Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Keras, or scikit-learn. Data Handling: Strong understanding of SQL, NoSQL, and big data tools (e.g., Spark, Hadoop). Cloud Platforms: Familiarity with AWS, Google Cloud, or Microsoft Azure for deploying ML models. Model Evaluation: Expertise in using metrics like accuracy, precision, recall, RMSE, or AUC-ROC for performance evaluation. Version Control: Experience with GitHub, GitLab, or other version control tools. Problem Solving: Strong analytical and problem-solving skills. Communication: Ability to explain complex AI/ML concepts to non-technical stakeholders. Preferred Skills and Qualifications Preferred Skills: Knowledge of MLOps frameworks such as Kubeflow or MLflow. Experience with natural language processing (NLP), computer vision, or time-series forecasting. Familiarity with APIs and microservices (e.g., FastAPI, Flask). Background in statistical modeling and probability theory. Understanding of bias detection and ethical AI principles. Keywords: continuous integration continuous deployment artificial intelligence machine learning rlang Texas AI Ml Engineer, Austin, TX [email protected] |
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| 04:37 AM 17-Dec-24 |