Kopius · 21 hours ago
Machine Learning Engineer
Valence is an innovative company focused on AI-driven coaching solutions for enterprises. They are seeking a Machine Learning Engineer to develop and optimize machine learning models for their conversational AI platform, directly impacting product performance and shaping the future of leadership coaching for Fortune 500 companies.
Information Technology
Responsibilities
You will develop scalable data pipelines, optimize models for performance and accuracy, and evaluate them to ensure they are production-ready
Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in new ways to advance product goals
Work with the product team to analyze user behavior and prioritize evolving requirements
Experiment at a high velocity, conducting statistical analyses, to optimize the end user experience
Research and development on new Conversational AI approaches leveraging cutting edge LLM/NLP advancements
Documentation of models, prompts, and processes to increase replicability and drive quality improvements
Stay current with the latest leading research advancements in ML, LLMs, and Conversational AI
Support other coding and feature development where required
Qualification
Required
Bachelor's degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
3+ years of professional experience (or equivalent) in software engineering, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field)
Practical experience and theoretical knowledge of language technologies such as: dialogue/conversational systems, NLP, and Information Retrieval
Strong foundation in data structures, algorithms, and software engineering principles
Proficiency in Python and relevant deep learning frameworks; training (e.g. PyTorch, Tensorflow, JAX, Hugging Face Transformers/Adapters), serving (e.g., Hugging Face TGI//outlines, vLLM)
Experience with LLM model development and deployment ideally including experience with model distillation, supervised fine-tuning using RLHF/DPO, and automatic prompt tuning (e.g. DSPy, TextGrad)
Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and associated ML services
Strong analytical and problem-solving skills
Experience structuring and running data-backed experiments
Strong written and verbal communication skills
Exposure to early-stage startups, preferably B2B SaaS
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