ML Engineer

As a highly skilled ML Engineer with 5+ years of experience, your role will involve designing and automating test solutions for API and UI workloads, troubleshooting production issues, and ensuring high-quality releases in an Agile environment. **Key Responsibilities:**

• **Algorithm Implementation:** Develop and implement unsupervised learning algorithms, specifically K-Means, to segment high-dimensional, unlabeled time-series datasets. - **Time Series Preprocessing:** Clean, transform, and normalize temporal data; handle missing values, outliers, and noise that can significantly impact K-Means performance. - **Feature Engineering for Time Series:** Extract relevant temporal features (e.g., rolling averages, trends, seasonality, spectral analysis) to convert time-series data into a format suitable for clustering. - **Model Optimization & Evaluation:** Determine the optimal number of clusters (K) using the elbow method or silhouette analysis. Optimize clustering performance by minimizing within-cluster variance. - **Pattern Recognition & Segmentation:** Analyze segmented data to identify unique, recurring behaviors or seasonal trends. - **Anomaly Detection:** Apply K-Means to identify anomalies by detecting data points that do not cluster with normal patterns. - **Production Deployment:** Deploy, monitor, and maintain ML models in production environments, ensuring scalability and efficiency. **Qualifications Required:**
• **Programming Languages:** Proficient in Python for building algorithms. - **Libraries & Frameworks:** Robust command over Scikit-learn (for K-Means), Pandas, NumPy, Matplotlib/Seaborn, and optionally TensorFlow or PyTorch. - **Mathematical Foundation:** Deep understanding of linear algebra, probability, and statistics. - **Time Series Analysis:** Proficiency in handling sequential data, including techniques for dimensionality reduction (PCA, t-SNE) before clustering. - **Data Engineering:** Experience with SQL and ETL processes. - **DevOps & MLOps:** Familiarity with Docker, Kubernetes, and model deployment practices. In addition to the technical requirements, you will benefit from a competitive salary and benefits package, a culture focused on talent development, and employee engagement initiatives such as project parties and Long Service awards. Persistent also promotes a values-driven, people-centric, and inclusive work environment where diversity and inclusion are actively fostered. Join Persistent to unleash your full potential! As a highly skilled ML Engineer with 5+ years of experience, your role will involve designing and automating test solutions for API and UI workloads, troubleshooting production issues, and ensuring high-quality releases in an Agile environment. **Key Responsibilities:**