Kadence is seeking a Lead Research Engineer to help build and scale next-generation AI systems that transform how professionals work with complex information. This high-impact role involves leading engineering standards, developing scalable ML systems, and collaborating with cross-functional teams to drive innovation and ensure robust solutions are delivered.
Responsibilities:
- Lead technically: Define engineering standards, shape architecture, and mentor engineers across ML initiatives
- Build end-to-end ML systems: From data pipelines → model development → deployment → monitoring
- Develop scalable infrastructure: Design high-performance systems for training and serving ML models in production
- Collaborate cross-functionally: Work closely with research scientists, product teams, and distributed engineering teams
- Drive innovation: Prototype new approaches and bring them into production environments
- Own delivery: Take responsibility for shipping robust, scalable solutions
Requirements:
- 8+ years of software engineering experience, with strong exposure to machine learning systems
- Deep expertise in Python and the ML ecosystem (NumPy, Pandas, PyTorch, scikit-learn, etc.)
- Proven experience building and deploying ML systems at scale
- Strong understanding of MLOps / ModelOps, including monitoring, automation, and lifecycle management
- Experience designing data pipelines and working with large-scale data processing frameworks
- Familiarity with cloud platforms (AWS, Azure, or similar) and distributed systems
- Background in Natural Language Processing (NLP), including areas like Information Extraction, Named Entity Recognition (NER), Information Retrieval
- Ability to translate research into production systems
- Experience mentoring engineers and leading technical workstreams
- Experience with knowledge graphs, LLMs, or advanced NLP systems
- Exposure to additional languages (Java, TypeScript, etc.)
- Strong grounding in probabilistic models and ML theory