Hybrid Applied AI Engineer

at Valence

• Job title: Applied AI Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Distributed Systems, Docker, Google Cloud Platform, Kubernetes, Numpy, Pandas, PySpark, Scikit-Learn, SQL
• Location requirements: Hybrid, New York City, United States

About the role

• Founding Applied AI Engineer defining AI-powered leadership coaching for enterprises. Collaborating with cross-functional teams to build intelligent systems at enterprise scale.

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.

Requirements

• 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
• Nice-to-have (but not required): experience with ML lifecycle tools (e.g., MLflow, Weights & Biases), familiarity with Cloud ML services, or past work building generative AI applications

Benefits

• Competitive salary including base + bonuses
• 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
• A culture built for top talent: intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together