Data & Ai - Ml Engineer

- Lead Machine Learning Engineer ML Architect Role Overview We are seeking a highly skilled Lead Machine Learning Engineer Architect with expertise in end-to-end ML pipeline design model training optimization and large-scale deployment The ideal candidate will bring 10 years of experience strong knowledge of ML frameworks scikit-learn PyTorch TensorFlow XGBoost LightGBM CatBoost and proven expertise in MLOps tools MLflow Kubeflow Azure ML Pipelines This role requires a balance of hands-on model engineering and technical leadership to deliver production-ready ML systems Key Responsibilities Machine Learning Model Development Build train and optimize models using scikit-learn PyTorch TensorFlow Keras XGBoost LightGBM and CatBoost Develop and test features using pandas NumPy and PySpark for large-scale datasets Apply advanced techniques for hyperparameter tuning model interpretability and ensemble methods Model Deployment Serving Deploy models to production using TensorFlow Serving TorchServe and ONNX TensorRT for optimized inference Design scalable APIs and endpoints for real-time and batch prediction services Implement containerized deployments Docker Kubernetes for portability and scalability MLOps Automation Build and manage ML pipelines using MLflow Kubeflow and Azure ML Pipelines Implement model versioning tracking and experiment management Establish CI CD workflows for ML models ensuring reproducibility and continuous improvement Optimization Performance Optimize models for latency throughput and cost efficiency in production environments Use ONNX TensorRT for inference acceleration and cross-platform model deployment Monitor deployed models for drift bias and performance degradation Leadership Collaboration Lead and mentor ML engineers and data scientists on best practices in ML and MLOps Collaborate with data engineering teams to ensure seamless integration with pipelines Partner with product managers and business stakeholders to design scalable AI-driven solutions Required Skills Qualifications 10 years of IT experience with hands-on ML AI engineering Expertise in Core ML frameworks pandas NumPy scikit-learn PySpark Advanced algorithms libraries XGBoost LightGBM CatBoost Deep learning TensorFlow Keras PyTorch Model optimization serving ONNX TensorRT TensorFlow Serving TorchServe Strong knowledge of MLOps tools MLflow Kubeflow Azure ML Pipelines Hands-on with cloud environments Azure AWS GCP and container orchestration Kubernetes Proven experience in leading ML projects mentoring teams and deploying production AI systems Preferred Skills Knowledge of distributed training strategies Horovod DDP Familiarity with feature stores Feast Tecton Databricks Feature Store Experience with responsible AI frameworks explainability fairness bias mitigation Exposure to multi-model orchestration and hybrid cloud ML architectures At DXC Technology we believe strong connections and community are key to our success Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing productivity individual work styles and life circumstances We re committed to fostering an inclusive environment where everyone can thrive Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services such as false websites or through unsolicited emails claiming to be from the company These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process nor ask a job seeker to purchase IT or other equipment on our behalf More information on employment scams is available