MLOPS Engineer

Join a leading-edge company that partners with Fortune 50 clients to deliver transformative retail and ecommerce solutions. We are at the forefront of innovation, helping global brands navigate the rapidly evolving digital landscape. Our team is composed of industry experts who are passionate about driving business success through strategic initiatives and cutting-edge technology.

Job Description

Job Description

We are seeking a dynamic Senior Software Engineer with an ML focus to lead the integration and operationalization of machine learning models in our Search area. This role requires collaboration with data scientists and leadership teams, and a strong foundation in MLOps methodologies. Experience in diverse ML platforms, including Google Vertex AI and other cloud and open-source technologies, is essential. The candidate will bridge MLOps, data science, and leadership to ensure the smooth functioning of our ML infrastructure.

Key Responsibilities

Diverse ML Platform Expertise:
• Maintain expertise in a range of ML technologies and platforms, with a preference for Google Vertex AI, but open to other systems as needed.
• Leverage support for open-source frameworks like TensorFlow, PyTorch, scikit-learn, and integrate them with ML frameworks via custom containers.
• Stay updated with the latest trends in MLOps and ML technologies.

Recommender System Design and Development:
• Hands-on experience working on recommender systems, drawing from ML techniques such as embedding based retrieval, reinforcement learning, transformers, and LLMs.
• Software engineering skills to work with teams integrating the recommender systems into customer facing products.
• Experience in AB testing and iterative optimization using data driven approaches.
• Understanding of infrastructure needs required to deploy ML systems (CPU/GPU, networking infrastructure).

Feature Store Management:
• Efficiently manage, share, and reuse machine learning features at scale using Vertex AI Feature Store.
• Implement feature stores as a central repository for maintaining transparency in ML operations across the organization.
• Enable feature delivery with endpoint exposure while maintaining authority and security features.

Data Management and Collaboration:
• Assist as needed with data labeling and management, ensuring high-quality data for ML models.
• Collaborate with data engineers and data scientists to ensure the integrity and efficiency of data used in ML models.
• Ensure end-to-end integration for data to AI, including the use of BigTable / BigQuery for executing machine learning models on business intelligence tools.

Continuous Monitoring and Optimization:
• Monitor ML systems in production, identify improvement opportunities, and implement optimizations.
• Participate in support rotations and participate in support calls as necessary.

About Golden Technology


Golden Technology was founded in 1997 with the goal of developing people and driving innovation. In other words, our aim is to pair world-class technologists like you with amazing companies that are doing impactful work.


After an initially slow start, and way too many late nights playing Final Fantasy 7, Golden Technology built a unique recruiting engine that would quickly prove itself to deliver top-tiered talent to fortune 500 clients across the US, time and time again.


Golden Technology has built a culture around family and helping the people we touch succeed in both their work and personal lives. Oh, everyone says that? Try us, you'll see it.


We're helping people find their calling and their dream jobs; and through our Golden Community initiatives we are actively working to improve the communities in which we work, live, and play.