Senior Research Engineer - Experimental Engineering

Consumer Reports•Yonkers, NY

8d•$115,000 - $160,000•Remote

About The Position

The Experimental Engineering team leads the engineering R&D efforts in new and emerging products at Consumer Reports. We're seeking a highly capable Senior Research Engineer to join our team and drive forward exploratory research engineering with particular focus on innovative applications of AI, machine learning, and emerging technologies. In this role, you’ll embark on ambitious early-stage engineering efforts, validate concepts through rapid prototypes, and translate timely experiments into actionable insights that guide Consumer Reports' strategic initiatives. Research engineers operate 6+ months ahead of product roadmaps. Your work will be essential to identifying opportunities and pushing our technological boundaries. This is a full-time remote opportunity, with hybrid work available for candidates local to Consumer Reports offices in New York or Washington, D.C. This position is not eligible for sponsorship or relocation assistance.

Requirements

Deep experience as a full-stack software engineer, with additional depth and interest in applied research, particularly within AI/ML domains.
Ability to take a vague problem and return with a crisp framing, a plan, and a working prototype without needing the path defined.
Motivated by entrepreneurial challenges, comfortable navigating ambiguity, and experienced in rapidly iterating early ideas to test feasibility and viability.
Comfortable being a senior voice on the team and making calls on technical direction, pushing back when something isn't worth building, and knowing when to kill a project.
Effectively communicate experimental findings and engineering insights clearly and enthusiastically to both technical and non-technical stakeholders.
Understand the balance between near-term product delivery and longer-term investment in innovation, and capable of operating effectively in early phases of product development (spike → proof-of-concept → early prototype).
Practical understanding or curiosity regarding consumer rights, consumer advocacy, product ethics, and how responsible AI can empower individuals.
7+ years of professional software engineering experience.
Demonstrated expertise in Python (particularly FastAPI), frontend development frameworks (ideally React and React Native) and AI orchestration.
Experience building and shipping applied AI products to consumers (building data pipelines, fine-tuning models, evaluating AI tools).
Demonstrated curiosity for solving challenging and non-straightforward engineering problems; this might be reflected in a prior research engineering position, contributions to open source projects, self-directed programming projects, or something you'll surprise us with.
A track record of designing and building innovative prototypes from the ground up, with examples you can walk through.
Exceptional problem-solving skills and the ability to clearly communicate technical concepts to cross-functional teams.
Experience mentoring other engineers or otherwise multiplying the work of a team.

Responsibilities

Lead exploratory spikes, proof-of-concept projects, and early-stage prototyping end-to-end to test high-impact, forward-looking ideas.
Identify strategic opportunities in emerging technologies (notably AI/ML) and translate these opportunities into actionable prototypes.
Serve as a technical leader on AskCR, our RAG chatbot built on Consumer Reports' product testing, journalism, and advocacy work and own architectural decisions on retrieval, evaluation, and orchestration.
Collaborate closely on technical planning, architecture, and implementation efforts for AskCR, our RAG chatbot built on Consumer Report’s product testing, journalism and advocacy work.
Work collaboratively across cross-functional teams (Digital Product, Product Testing, User Research, Data Engineering, Advocacy) to share insights and ensure learnings are leveraged broadly across Consumer Reports.
Establish and refine practices for documenting experiments and synthesizing research outputs to maximize their organizational impact.
Mentor engineers and raise the technical bar across the team.
Cultivate a culture of curiosity, experimentation, rapid learning, and discovery.