AI Engineer

🕒 June 5

🇺🇸 United States – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 AI Engineer

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OneMagnify

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1967

🤝 B2B

🛍️ eCommerce

🤖 Artificial Intelligence

B2B • eCommerce • Artificial Intelligence

OneMagnify is a company focused on creating optimal customer experiences through digital transformation. They specialize in a variety of services including customer research, brand experience, UI/UX design, website development, eCommerce, and programmatic media powered by AI. By leveraging data-driven strategies and technology, OneMagnify enhances customer engagement and develops personalized experiences at scale for their clients.

📋 Description

• Build and Maintain Production ML/AI Pipelines • Design and maintain production ML and AI pipelines, including training, evaluation, deployment, and monitoring. • Create data pipelines and prepare datasets for AI consumption. • Develop scalable model serving architectures for real‑time and batch inference. • Ensure AI and LLM systems are production‑ready, stable, and performant. • Apply MLOps Best Practices • Implement experiment tracking, model versioning, and reproducible training workflows. • Establish processes for continuous evaluation and improvement of machine learning and generative AI systems. • Support reliable lifecycle management of models from experimentation through deployment and iteration. • Monitor, Observe, and Improve Models in Production • Build and maintain monitoring systems to detect data drift, performance degradation, and operational issues. • Use evaluation frameworks and monitoring signals to guide model improvements over time. • Help teams respond to production issues with clear diagnostics and remediation approaches. • Be a Trusted Technical Partner to Clients • Work directly with clients to explain AI concepts, tradeoffs, and outcomes in clear, practical terms. • Contribute to strong client relationships through thoughtful solutioning and consistent delivery. • Present technical approaches and results to both technical and non-technical stakeholders. • Collaborate Across Integrated Teams • Work closely with data scientists and AI engineers to operationalize models effectively. • Partner with software engineers to ensure smooth deployment and integration into client platforms. • Collaborate with analytics, strategy, and delivery teams to align MLOps solutions with client objectives. • Support Client-Facing Delivery • Contribute to client discussions by explaining MLOps approaches, tradeoffs, and outcomes in practical terms. • Help translate client requirements into operational AI solutions that can scale and evolve. • Support consistent, high‑quality delivery across multiple client engagements.

🎯 Requirements

• Bachelor’s degree in a relevant field or equivalent practical experience; Master’s degree preferred. • 2+ years in a technical role focused on machine learning, data platforms, or AI systems (2+ years post‑Master’s if applicable). • Hands-on experience deploying and operating machine learning or generative AI models in production environments. • Strong understanding of MLOps practices, including experiment tracking, model versioning, and monitoring. • Experience building data and model pipelines in distributed environments. • Familiarity with model evaluation frameworks and performance monitoring techniques. • Exposure to large language models and applied AI use cases. • Strong object-oriented programming skills. • Working knowledge of Databricks. • Proficiency with Python, SQL, and related analytics or engineering tools; familiarity with BI tools such as Tableau, Power BI, or Domo is a plus. • Experience owning or leading technical workstreams in collaborative environments. • Clear communication skills, including the ability to explain technical concepts to non‑technical stakeholders. • Experience in integrated marketing, digital agency, marketing services, or consulting environments preferred.

🏖️ Benefits

• medical, dental, and vision coverage • 401(k) retirement plan • paid holidays • Flexible Time Off (FTO) • additional programs focused on wellness, financial security, and professional growth