Intermediate Applications Developer

Role Overview: As a Senior Machine Learning Engineer at UPS, you will be part of the Machine Learning Engineering team responsible for utilizing your expertise in data science, software engineering, and AI to build next-generation intelligent systems. You will play a crucial role in designing, developing, and deploying ML models and pipelines that drive business outcomes, working closely with data scientists, software engineers, and product teams to align with UPS's strategic goals. Key Responsibilities: - Design, deploy, and maintain production-ready ML models and pipelines for real-world applications. - Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm. - Implement automated retraining, drift detection, and re-deployment of ML models. - Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML. - Implement model monitoring, observability, and alerting across accuracy, latency, and cost. - Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases. - Ensure pipelines are secure, compliant, and cost-optimized. - Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance. - Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap. - Stay current with the latest ML research and apply new tools pragmatically to production systems. - Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems. Qualifications Required: - Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus). - 5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems. - Proficiency in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL. - Experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML). - Familiarity with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow). - Practical exposure to big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop). - Strong understanding of statistical methods, ML algorithms, and deep learning architectures. Additional Details of the Company: UPS is committed to providing a workplace free of discrimination, harassment, and retaliation. Role Overview: As a Senior Machine Learning Engineer at UPS, you will be part of the Machine Learning Engineering team responsible for utilizing your expertise in data science, software engineering, and AI to build next-generation intelligent systems. You will play a crucial role in designing, developing, and deploying ML models and pipelines that drive business outcomes, working closely with data scientists, software engineers, and product teams to align with UPS's strategic goals. Key Responsibilities: - Design, deploy, and maintain production-ready ML models and pipelines for real-world applications. - Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm. - Implement automated retraining, drift detection, and re-deployment of ML models. - Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML. - Implement model monitoring, observability, and alerting across accuracy, latency, and cost. - Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases. - Ensure pipelines are secure, compliant, and cost-optimized. - Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance. - Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap. - Stay current with the latest ML research and apply new tools pragmatically to production systems. - Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems. Qualifications Required: - Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus). - 5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems. - Proficiency in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL. - Experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML). - Familiarity with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow). - Practical exposure to big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop). - Strong understanding of statistical methods, ML algorithms, and deep learning architectures. Additional Details of the Company: UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.