We all witness the inefficiencies in how the public sector spends money. These inefficiencies hit hardest in critical areas such as national security, education, homelessness, and infrastructure, impacting the very fabric of our communities. We believe the root cause of public sector inefficiency lies in a broken procurement process that forces innovative, private companies to walk away from public sector opportunities. When red tape blocks innovation, taxpayers’ dollars are wasted, businesses can’t scale, and communities miss out on transformative improvements.
At Starbridge: we are building the future of public sector go-to-market. We envision a world where public contracts are transparent and accessible to all. One where any entrepreneur or business can understand the market, find opportunities, and compete on the merits of the product. Our mission at Starbridge is to catalyze a new era of public-private partnerships that change the world for the better.
Starbridge's Revenue AI Platform helps businesses grow public sector revenue. By identifying early buying signals, building strategic outbound capabilities, and automating manual processes like proposal writing, our partners win more contracts & establish a competitive edge.
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
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