Sr. Machine Learning Software Engineer

Key Responsibilities

• 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.

Preferred Skills:

Not looking for a Data Scientist. Looking for someone with an engineering background with a strong Machine Learning focus or interest.

• Experience working collaboratively with data science teams, understanding their needs and challenges.
• Ability to lead initiatives and communicate effectively with technical teams and senior leadership.
• Proven ability to understand company business problems and identify probable technical solutions to those problems.
• Familiarity with a range of ML tools and frameworks, and openness to adapting to emerging technologies.