Qualifications
What Makes You a Great Fit:
Solid understanding of classical machine learning fundamentals, with an emphasis on model functionality beyond just API calls.
A strong evaluative mindset: you conceive the measurement system prior to initiating the first prompt and consider evaluations as vital engineering artifacts.
Hands-on experience with search and retrieval methods: dense, sparse, hybrid, reranking, and query understanding, utilizing managed tools effectively.
Practical familiarity with agentic architectures, including tool usage, orchestration, and failure recovery.
A safety-first approach, implementing guardrails and content policies, ensuring graceful degradation amidst uncertainty.
Experience in managing production ML processes: observability, latency budgets, cost tracking, and regression detection.
About the job
About Our Team: Join the expanding Financial Assistant team at Platacard, where we are dedicated to creating intelligent systems designed to empower users in managing their finances, grasping spending habits, and seamlessly interacting with financial products. Our team is integral to enhancing customer experience, engagement, and the overall value of our core offerings. Operating in a regulated environment, we prioritize accuracy, safety, and trust.
Utilizing AWS, Go, Python, and cloud-based models, we remain adaptable, integrating both off-the-shelf tools and custom solutions. Our focus is on crafting systems that yield significant and valuable results for our organization.
As a pivotal member of our cross-functional team, you will collaborate with backend, mobile, and LLM engineers to drive innovation.
About Platacard
At Platacard, we are committed to leveraging technology to revolutionize the financial landscape for our users. Our Financial Assistant team is at the forefront of this mission, dedicated to building systems that not only meet regulatory standards but also enhance user engagement and trust.
