Job Title: Senior Machine Learning Engineer (Generative AI & Cloud Platforms)

We are looking for a collaborative, hands-on Senior Machine Learning Engineer to join our product team. In this role, you will contribute to the software design, algorithm design, and overall product lifecycle for innovative, user-centric AI solutions.

Our engineering process is highly collaborative and agile. You will pair daily with cross-functional team members, review code based on best practices, and build scalable machine learning systems that drive real business value. If you thrive in a fast-paced, innovative environment and have a passion for production-grade GenAI, cloud-native architecture, and modern MLOps, we want to hear from you., <>Delivery & Execution (70%)

• Collaborate and pair daily with product team members (UX, engineering, and product management) to design and build secure, reliable, scalable machine learning solutions.
• Architect and implement cutting-edge AI/ML algorithms, Agentic AI applications, and Retrieval-Augmented Generation (RAG) workflows.
• Design and develop enterprise knowledge layers utilizing knowledge graphs, semantic search, and vector databases.
• Write clean, maintainable code and automated scripts for infrastructure, monitoring services, and test cases, including “destructive testing” to ensure production resiliency.
• Create meaningful dashboards, logging, and alerting systems to proactively track and address issues.
• Document and review code to ensure adherence to high quality, security, and change control standards.

<>Support & Enablement (20%)

• Provide robust application support for software running in production, monitoring Service Level Objectives (SLOs) and prediction quality.
• Proactively evaluate the performance and capacity of production code, infrastructure, data pipelines, and message processing.
• Field technical questions from product and support teams while driving cross-team collaboration.

<>Learning & Continuous Improvement (10%)

• Participate actively in communities of practice around modern software design, machine learning, and core development practices.
• Proactively explore new technologies, frameworks, and industry best practices.

• Experience: 5+ years of professional experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related field, with a proven track record of deploying production-grade AI solutions.
• GenAI & LLMs: Hands-on experience building Agentic AI applications, LLM-powered solutions, RAG systems, and intelligent automation workflows.
• Data & Knowledge Layers: Strong experience with knowledge graphs, graph engineering, network analysis, semantic search, and combining structured/unstructured data.
• Core Languages & Frameworks: Proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn, Pandas).
• Cloud & MLOps: Experience with cloud-native AI/ML platforms, preferably Google Cloud Platform (Vertex AI, BigQuery, BigQuery ML), containerization, and vector databases.
• Software Engineering Best Practices: Solid understanding of CI/CD, version control, automated testing, security, and performance optimization across large-scale data systems (SQL, NoSQL).
• Education: Minimum high school diploma and/or GED (relevant technical degree preferred)., * Global Perspective & Managing Ambiguity
• Nimble Learning & Self-Development
• Strong Collaboration & Interpersonal Savvy
• Communicates Effectively
• Cultivates Innovation & Drives Results
• Situational Adaptability