Kopius · 7 hours ago
Applied AI Engineer
Valence is pioneering an AI-native coaching platform for enterprises, focusing on transforming how organizations approach learning and development. As an Applied AI Engineer, you will design and build AI-powered leadership coaching systems, working closely with cross-functional teams to deliver personalized coaching at scale.
Information Technology
Responsibilities
Architect and build enterprise-grade AI and conversational systems that power coaching workflows and user experiences
Develop, evaluate, and refine LLM-based components - balancing performance, scalability, and reliability in real use cases
Integrate and manage diverse sources of structured and unstructured data to improve contextual understanding and output quality
Partner closely with product, engineering, and design to translate user needs into impactful technical solutions
Rapidly prototype and iterate on systems that span backend services, data pipelines, and frontend interactions as needed
Build tooling, tests, and automation to support reliable model deployment, observability, and continuous improvement
Help streamline data and science workflows, enabling fast experimentation and data-driven decisions
Qualification
Required
3+ years of experience in software engineering, AI/ML, data-intensive systems, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field)
Familiarity with language systems (e.g., NLP, conversational interfaces, IR) and comfort reasoning about model behavior, context, and evaluation - both theoretical and practical knowledge
Experience with core data science tools such as NumPy, scikit-learn, Pandas, PySpark, plus SQL and common visualization tools (e.g., matplotlib, Seaborn, Plotly, or BI tools) to explore and communicate insights
Comfortable developing and deploying services in cloud environments (AWS, GCP, Azure) and working with containerization/orchestration (Docker, Kubernetes)
Strong software engineering skills, including writing maintainable code, debugging distributed systems, and collaborating in cross-functional teams
Eagerness to tackle unfamiliar problems, learn new technologies, and contribute to shaping our platform and culture
Ability to explain technical ideas clearly and work effectively with both technical and non-technical stakeholders
Preferred
Experience with ML lifecycle tools (e.g., MLflow, Weights & Biases)
Familiarity with Cloud ML services
Past work building generative AI applications
Benefits
Comprehensive health coverage (medical, dental, vision) from day one
Generous PTO, company-wide R&R shutdowns, and paid parental leave
Retirement plan support for US and global employees
Meaningful ownership in a venture-backed company at a growth inflection point
Financial upside that comes from scaling fast
Top-up grants as we scale and you deliver exceptional performance — your compensation grows alongside your impact