Valence

Applied AI Engineer

Valence

full-time

Posted on:

Location Type: Hybrid

Location: New York City • New York • United States

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Tech Stack

AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformKubernetesNumpyPandasPySparkScikit-LearnSQL

About the role

  • 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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AIMLdata-intensive systemsNLPconversational interfacesNumPyscikit-learnPandasPySparkSQL
Soft Skills
collaborationproblem-solvingcommunicationadaptabilitytechnical explanation
Certifications
Master's in Computer SciencePh.D. in Computer ScienceMaster's in MLMaster's in Data Science