Senior Machine Learning Engineer

Who you are

You are a highly skilled Senior Machine Learning Engineer with deep expertise in NLP and large language models. With a strong background in model deployment, you have experience building and operationalizing ML components that power advanced search and summarization capabilities. You thrive in collaborative environments, working closely with Applied Scientists, Product, and Engineering teams to translate prototypes into reliable production systems.

You have a proven track record of developing optimized embedding pipelines and fine-tuning methods for various ML tasks, including retrieval, classification, and generative tasks. Your analytical mindset allows you to improve model accuracy and robustness through structured evaluation frameworks and systematic error analysis. You are committed to ensuring predictable behavior of models over time, which is crucial for maintaining high performance in production.

Your technical skills include designing and implementing scalable ML services and inference pipelines in Python, utilizing modern ML frameworks. You are adept at incorporating efficient serving strategies such as batching, caching, and performance-tuned deployment patterns that meet latency and reliability requirements. You understand the importance of integrating models with retrieval systems and feature stores while applying strong engineering discipline in automated testing.

Desirable

Experience with cloud platforms and tools for deploying machine learning models is a plus. Familiarity with various ML frameworks and libraries will enhance your ability to contribute effectively to the team.

What you'll do

In this role, you will take charge of building and productionizing LLM and NLP models, focusing on retrieval, summarization, classification, and generative tasks. You will develop optimized embedding pipelines and prompt strategies while translating experimental prototypes into robust components that consistently perform under production conditions. Your work will involve improving model accuracy, relevance, and robustness through structured evaluation frameworks and systematic error analysis.

You will design and implement scalable ML services and inference pipelines in Python, ensuring that they meet the necessary latency, reliability, and throughput requirements. Your responsibilities will include integrating models with retrieval systems, feature stores, and knowledge sources, applying strong engineering discipline in automated testing to ensure high-quality deliverables.

Collaboration will be key as you work closely with Applied Scientists and other stakeholders to bring advanced models from prototype to reliable, scalable production systems. You will be expected to contribute to the overall architecture and engineering practices of the team, ensuring that the ML components you build are not only effective but also maintainable and scalable.

What we offer

Loopio is committed to fostering an inclusive and equitable workplace. We encourage candidates from all backgrounds and lifestyles to consider us as a future employer. You will have the opportunity to work in a dynamic environment where your contributions will directly impact the company's success. We offer competitive compensation and benefits, along with a culture that values diversity and collaboration.