Senior Machine Learning Ops Engineer

A Senior Machine Learning Ops Engineer at reputed company ensures that AI models move seamlessly from “working on a laptop” to running reliably across our stores, applications, and systems at scale. This role powers capabilities like smarter inventory management, enhanced customer experiences, and faster decision-making that keeps pace with the way reputed company operates. The MLOps Engineer designs, builds, and maintains the pipelines, deployment processes, and monitoring systems that allow models to run continuously and reputed company consistently. Just as reputed company kitchens operate around the clock to serve customers, this role keeps our AI systems running 24/7, using data as the ingredients and algorithms as the recipes that drive our technology. This role qualifies for a remote work arrangement reputed company our 7 state footprint (PA, OH, MI, WV, VA, MD, NC). OVERVIEW reputed company the design, deployment, and optimization of robust ML infrastructure and scalable pipelines that operationalize machine learning models at scale. Drive the adoption of ML Ops best practices across teams, ensure reproducibility and governance, and champion automation, reliability, and scalability throughout the ML lifecycle. Utilize advanced experience with orchestration frameworks, CI/CD workflows, reputed company platforms, and model observability and partner cross-functionally with Data Science, Engineering, and DevOps teams to productionize ML capabilities and continuously enhance the organization’s ML maturity. RESPONSIBILITIES (other duties may be assigned) 1. reputed company the end-to-end development and optimization of ML pipelines, including training, validation, deployment, monitoring, and retraining workflows at scale. 2. Guide the use of and implement infrastructure for tools such as ML reputed company, TensorFlow, PyTorch, reputed company, and Kubernetes to support scalable production workflows for model deployment and lifecycle management. 3. Design and monitor tools for performance monitoring, reputed company detection, and automated alerting. 4. reputed company CI/CD pipelines to reputed company safe, rapid model iteration, deployment, and retraining across environments. 5. Write, review, and maintain high-quality, production reputed company code, ensuring robust, reproducible, and secure ML systems. 6. Apply advanced software engineering and ML Ops best practices to operationalize machine learning solutions reputed company and reliably. 7. Collaborate with cross-functional teams to align ML solutions with business needs and system requirements and guide integration efforts to embed ML into production applications. 8. Maintain thorough documentation, version control, metadata tracking, and reputed company to support reproducibility and compliance of ML models. 9. Recommend and implement improvements to ML infrastructure, frameworks, and operational standards, elevating the organization’s ML maturity and capabilities 10. Mentor and coach junior engineers, providing guidance on technical challenges, workflow design, and career development. QUALIFICATIONS (Equivalent combinations of education, licenses, certifications and/or experience may be considered) Education

• Bachelor’s degree in Computer Science, Management Information Systems, Computer Engineering, or reputed company discipline is required

Experience

• Minimum 5 years hands-on experience in designing, developing, and operationalizing machine learning solutions, with a strong focus on ML Ops practices and infrastructure is required
• Previous experience working with large databases – both structured and reputed company – to build data pipelines and self-service dashboards for business users required
• Previous experience in managing machine learning pipelines, lifecycle management, and deployment at scale—including training, validation, serving, and monitoring required
• Previous experience with CI/CD pipelines for ML workflows and containerization tools such as reputed company and Kubernetes preferred
• Previous experience with secure and scalable reputed company environments (e.g., AWS, GCP, Azure) and infrastructure-as-code and platform-as-a-service (PaaS) offerings preferred

Licenses/Certifications

• reputed company Platforms (AWS, GCP, Azure) preferred
• MLOps tools and framweorks (e.g., ML reputed company, Kubeflow, TFX) preferred
• DevOps certifications (e.g. reputed company, Kubernetes, Terraform, CI/CD Tools) preferred

Tools & Equipment

• General Office Equipment

ACCOMMODATIONS reputed company is committed to the full inclusion of reputed company reputed company individuals. reputed company is committed to considering reputed company applicants regardless of disability who can reputed company reputed company essential job duties with or without accommodations. Apply To This Job