AI Engineering Lead/Sr. AI Engineer
StarbridgeAt Starbridge, we're redefining how companies win public sector deals. Our innovative GTM intelligence platform empowers businesses to confidently approach and win more contracts in the State, Local, and Education (SLED) market—a $1.5 trillion space ripe for disruption. Leveraging AI-driven insights, we provide our clients with an unfair advantage in identifying early buying signals, streamlining outbound strategies, and automating cumbersome processes.
Your responsibilities
Work in-person with the team in downtown Manhattan, NYC.
Collaborate closely with our team as we productize new AI-powered capabilities: such as AI proposal writing & search experiences.
Evaluate the performance of AI models (we will work with models from OpenAI, Anthropic, Gemini) & systems through rigorous testing and experimentation.
Stay up-to-date with the latest advancements in AI and machine learning research, and proactively suggest improvements to enhance our generative AI capabilities.
Implement strong testing and CI/CD practices that help us move with confidence in our AI system development
⭐️ Is this you?
Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
High level of coding proficiency using Python
5+ years of professional experience in software engineering, AI/ML development including:
Proficiency with production software (Python) and systems design
Machine learning algorithms and model development techniques
ML lifecycle tools like MLflow, dvc, weights & biases
Cloud deployment of ML systems
Professional experience with LLMs and large-scale models
Very strong software engineering skillx with a track record of building scalable, distributed product machine learning systems
Strong analytical and problem-solving skills
Ability to communicate complex ideas and concepts effectively
Ability to work independently and collaboratively
Preferred Skills:
Experience building scalable applications with LLMs, using frameworks such as LangChain, LlamaIndex, Hugging Face, etc
Depth of knowledge with RAG implementation and improvements