Highlights
Reliable systems, scalable solutions, cross-functional collaboration.
Description
Job Summary
pJoin OneMagnify as an AI Engineer and contribute to the development of reliable, scalable, and production-ready machine learning and generative AI systems. You’ll work closely with data scientists and engineers to operationalize models across various platforms.
Responsibilities
- Build and maintain production ML/AI pipelines.
- Implement MLOps best practices including experiment tracking and model versioning.
- Monitor, observe, and improve models in production environments.
- Collaborate with cross-functional teams to integrate AI systems into client platforms.
- Support client-facing delivery by explaining technical concepts clearly.
Required Skills
- MLOps practices
- Experiment tracking
- Data pipeline development
- Model monitoring and evaluation
- Python programming
Required Skills Explained
- 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.
Who is this for
pThis role is ideal for experienced AI engineers who enjoy hands-on engineering work and are passionate about leveraging AI to drive business outcomes in complex, real-world environments.
Why This Job is a Good Opportunity
ulliJoin a company that blends data, technology, and creativity to drive measurable business outcomes for clients.liWork in an innovative environment where you'll contribute to operationalizing models across digital, analytics, and marketing platforms.liPotential to collaborate with diverse teams and impact real-world business decisions through AI solutions.liGrowth opportunities within a dynamic organization focused on delivering integrated MLOps practices.
Interview Preparation Tips
- Prepare examples of your experience deploying and operating machine learning models in production environments.
- Discuss your familiarity with MLOps best practices, such as experiment tracking and model versioning.
- Showcase your ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
- Highlight any experience you have with Databricks or large language models like GPT.
Career Growth in This Role
pThe role of an AI Engineer at OneMagnify offers significant opportunities for career growth. You can deepen your expertise in MLOps and generative AI systems, contributing to the development and operationalization of cutting-edge solutions. As you advance, you may take on more leadership roles within the team or explore specialized areas such as data science, engineering, or client-facing delivery. The company's focus on integrated solutions provides a platform for continuous learning and skill enhancement.
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Skills
Frequently Asked Questions
What is the role of an AI Engineer at OneMagnify?As an AI Engineer, you will focus on building production-ready machine learning pipelines and ensuring models are reliable and scalable for real-world use.
Do I need experience with Databricks or Tableau to apply?While not mandatory, familiarity with tools like Databricks and Tableau is a plus. We value hands-on experience in deploying AI systems more than specific tool knowledge.
What kind of support will I get for client-facing delivery?You’ll work closely with clients to explain technical concepts clearly and contribute to strong, client-focused solutions.
