Senior Machine Learning Engineer

The Senior Machine Learning Engineer is responsible for designing, developing, testing and operationalizing ML (Machine Learning) and other data solutions, including cloud-based or internet-related tools for internal or external consumption. The incumbent will provide technical solutions to enable the company to meet its strategic objectives through effective collaboration with business analysts, data scientists, software engineers, platform engineers, quality assurance testers, and project managers. The incumbent will collaborate with others to ensure successful teamwork, effective development, and delivery of high-quality machine learning and data solutions that include MLOps practices such as CI/CD pipelines, automated testing, and monitoring

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Qualifications

Education and Experience

Required:

• Bachelor's Degree in Computer Science or Computer Engineering or in lieu of a degree, at least 7 years of experience in software development
• 4+ years of experience in ML, MLOps, and/or software development
• In-depth knowledge of software development life cycle (SDLC) methodologies and practices, particularly MLOps and DevOps
• In-depth knowledge of software development tools, platforms and languages, particularly cloud platforms
• Experience in developing, integrating, testing and deploying software solutions for cloud-based or internet-related tools
• Knowledge of relational databases and SQL
• Excellent written and verbal communication skills
• Experience in developing Microservices and in-depth knowledge of various Integration patterns
• Must be eighteen years or older
• Must be legally authorized to work in the United States without company sponsorship

Preferred

• Databricks experience
• Supply chain experience
• R&D experience
• AI implementation experience be it RAG/TAG/other generative or agentic workloads
• SW experience preferred

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Responsibilities

• Design, develop, and deploy machine learning models and other data solutions in alignment with business requirements and technical specifications defined
• Train, validate, and optimize machine learning models and other data solutions to ensure high performance and accuracy. Implement techniques for model/solution improvement and fine-tuning.
• Write high-quality, maintainable, and scalable code
• Create and maintain technical documentation including model development processes, deployment workflows, operational procedures, code comments, design documents, and user manuals
• MLOps Implementation: Develop and maintain CI/CD pipelines for seamless model deployment. Drive testing throughout the development, integration, deployment, and management of the software solution, and automating where possible to ensure solution quality and security in accordance with industry standards and company policies
• Collaborate with data scientists, business analysts, software engineers, IT operations, quality assurance testers, and project managers to to translate business requirements into successful technical solutions that are integrated into production environments
• Provide ongoing solution support including incident and problem management, root cause analysis, request fulfilment, security compliance, fault repair, resiliency testing, and observability
• Innovation and Research: Stay updated with the latest advancements in machine learning and MLOps practices. Explore and implement innovative solutions to enhance the company’s machine learning capabilities.

This is not a remote/hybrid position, and will report to our headquarters in Cleveland, OH

This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa. Must be legally authorized to work in the country of employment without needing sponsorship for employment work visa status now or in the future.

Job duties include contact with other employees and access confidential and proprietary information and/or other items of value, and such access may be supervised or unsupervised. The Company therefore has determined that a review of criminal history is necessary to protect the business and its operations and reputation and is necessary to protect the safety of the Company’s staff, employees, and business relationships.