Job Summary
Job Summary We are seeking a highly skilled Machine Learning Engineer to design, build, and deploy scalable ML solutions for real-world business problems. The ideal candidate should have expertise in Python, Apache Spark, Apache Kafka, Machine Learning & Statistical Modeling, and Time Series Algorithms. This role involves working with large-scale data pipelines, developing predictive models, and collaborating with cross-functional teams to deliver production-grade AI/ML solutions. Key Responsibilities 1. Machine Learning Model Development Design, build, train, and optimize machine learning models for predictive and prescriptive analytics. Apply statistical modeling techniques to solve complex business and operational problems. Develop and evaluate supervised, unsupervised, and forecasting models. Implement time series algorithms for forecasting, anomaly detection, and trend analysis. Perform feature engineering, model validation, and hyperparameter tuning. 2. Data Engineering & Pipeline Development Build and maintain scalable data processing pipelines using Apache Spark. Use Apache Kafka for real-time data ingestion and streaming use cases. Process structured and unstructured datasets for ML model training and inference. Ensure data quality, consistency, and performance across pipelines. Integrate data from multiple sources into a unified analytics environment. 3. Production Deployment & Monitoring Deploy ML models into production environments and support their lifecycle management. Monitor model performance, drift, and retraining requirements. Collaborate with engineering teams to integrate ML services into applications and business platforms. Optimize model inference and pipeline performance for scalability and reliability. 4. Research & Analysis Research and implement advanced ML techniques and algorithms. Analyze trends and patterns in large datasets to identify business opportunities. Develop forecasting models using time series analysis such as ARIMA, Prophet, LSTM, or similar methods. Translate business problems into analytical and machine learning solutions. 5. Collaboration & Documentation Work closely with Data Engineers, Product Managers, Analysts, and Business Stakeholders. Document model assumptions, methodologies, pipelines, and deployment processes. Present findings, model insights, and recommendations to technical and non-technical teams. Participate in architecture discussions, code reviews, and Agile ceremonies. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field. Strong hands-on experience in Python for machine learning and data processing. Experienc
Key Responsibilities
2. Integrate and process large-scale streaming data with Apache Kafka and Spark, enabling real-time model training and inference.
3. Evaluate machine learning models using cross-validation, ROC/AUC, Precision/Recall, F1-score, and confusion matrix to ensure robust predictive performance.
4. Apply advanced NLP techniques with NLTK and SpaCy to extract and preprocess relevant features for forecasting tasks.
5. Optimize model deployment pipelines using Apache Airflow and Hadoop, ensuring efficient workflow orchestration and data management.
6. Collaborate within the development team to troubleshoot, refine, and enhance ML solutions, ensuring adherence to best practices and coding standards.
Skill Requirements
2. Strong Skills In Python Programming, Including Numpy, Pandas, Scikitlearn, Tensorflow, Pytorch, Xgboost, And Lightgbm.
3. Indepth Knowledge Of Distributed Data Processing With Apache Spark And Realtime Data Integration Using Apache Kafka.
4. Solid Understanding Of Ml Model Evaluation Metrics And Techniques, Including Crossvalidation And Performance Optimization.
5. Experience With Workflow Orchestration Tools Such As Apache Airflow And Big Data Platforms Like Hadoop.
6. Advanced Proficiency In Nlp Libraries Including Nltk And Spacy.
Other Requirements
2. Certifications Such As Tensorflow Developer Certificate
3. - Aws Certified Machine Learning � Specialt