Top Tech Jobs & Startup Jobs in NYC, NY

Software Engineering interns contribute to production features, applications, APIs, services, data ingestion pipelines, and machine-learning-enabled products. They participate in code reviews, deployment, observability, infrastructure as code, and production-readiness practices while collaborating with experienced engineers. Interns work in person from the Cambridge headquarters or New York City office and receive opportunities for technical learning, exploration, and cross-team development.

Develop and test machine learning models, pipelines, agentic systems, and LLM-powered applications under senior-engineer mentorship. Interns will work across the ML lifecycle, including problem framing, model selection, pipeline development, evaluation, and deployment support. The role involves collaborating with ML Engineers, Product Managers, Designers, and Full-Stack Engineers on scalable AI solutions.

Own AI partnership development and a portfolio of strategic clients. Manage partner relationships, coordinate cross-functional launches, drive product adoption and expansion, convert trials, support renewals, and resolve partnership or client issues. The role requires technical fluency in AI/ML, APIs, and software implementation, along with strong communication, senior relationship management, commercial judgment, and comfort operating autonomously in ambiguous environments. Approximately 25% travel is required within the United States and to company hubs.

Design, build, and productionize agentic AI systems and retrieval pipelines for financial data. Participate across the ML lifecycle: framing, experimentation, deployment, monitoring, and evaluation. Collaborate with cross-functional teams to integrate proprietary structured and unstructured data, improve agent performance, and automate MLOps workflows for scalable, robust AI-driven products.

Design, build, and scale production RAG systems and retrieval pipelines integrating chunking, embeddings, vector databases, and LLM orchestration. Optimize vector search, indexing, and evaluation; collaborate with product, design, and MLOps to deploy and maintain end-to-end ML solutions.

Drive market expansion and adoption of Kensho's AI products by bridging technical AI capabilities and commercial strategy. Lead go-to-market planning, customer demos, co-development partnerships, market analysis, sales enablement, and cross-functional alignment to translate customer needs into product and roadmap priorities.

Design and build AI-centric full‑stack TypeScript web applications (SPAs and APIs). Collaborate on product and architecture, own technical decisions, mentor peers, perform code reviews, and manage project priorities and deliverables.

The Senior Backend Software Engineer develops secure APIs utilizing Kensho's AI capabilities, collaborates across teams, and mentors colleagues while managing project deadlines and deliverables.

As an MLOps Engineer II, you'll enhance ML workflows, support engineers, improve model deployment processes, and advocate for best practices across teams.