Senior Technical Lead - Traditional ML

Experience: Not Available to Not Available years

Location: Hyderabad, India

Skills: Python, Apache Spark, Apache Kafka, Machine Learning, Statistical Modeling, Time Series Algorithms, scikit-learn, TensorFlow, StatsModels, Numpy, Pandas, Pytorch, Xgboost, Lightgbm, NLP, NLTK, SpaCy, Apache Airflow, Hadoop

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.




• Develop and implement time series forecasting models using Python, scikit-learn, TensorFlow, and StatsModels, optimizing for accuracy and scalability.
• Integrate and process large-scale streaming data with Apache Kafka and Spark, enabling real-time model training and inference.
• Evaluate machine learning models using cross-validation, ROC/AUC, Precision/Recall, F1-score, and confusion matrix to ensure robust predictive performance.
• Apply advanced NLP techniques with NLTK and SpaCy to extract and preprocess relevant features for forecasting tasks.
• Optimize model deployment pipelines using Apache Airflow and Hadoop, ensuring efficient workflow orchestration and data management.
• Collaborate within the development team to troubleshoot, refine, and enhance ML solutions, ensuring adherence to best practices and coding standards.

Skill Requirements
• Advanced Proficiency In Machine Learning And Natural Language Processing, With Solid Experience In Time Series Analysis And Forecasting.
• Solid Skills In Python Programming, Including Numpy, Pandas, Scikitlearn, Tensorflow, Pytorch, Xgboost, And Lightgbm.
• Indepth Knowledge Of Distributed Data Processing With Apache Spark And Realtime Data Integration Using Apache Kafka.
• Solid Understanding Of Ml Model Evaluation Metrics And Techniques, Including Crossvalidation And Performance Optimization.
• Experience With Workflow Orchestration Tools Such As Apache Airflow And Big Data Platforms Like Hadoop.
• Advanced Proficiency In Nlp Libraries Including Nltk And Spacy.

Other Requirements
• Optional But Valuable:
• Certifications Such As Tensorflow Developer Certificate
• AWS Certified Machine Learning – Specialty

📌 Senior Technical Lead Traditional ML (Secunderabad)
🏢 HCL Technologies
📍 Secunderabad