Member of Technical Staff

Engineering, Full-time

San Francisco, CA

Reports to CEO / Founders

We encourage you to apply even if you don't meet 100% of the requirements

Mixedbread is an applied AI research and technology company building next-generation information retrieval systems for modern AI applications. Our work spans multimodal and multilingual retrieval, embedding and search models, LLM-augmented retrieval, evaluation systems, agentic search, and high-performance AI infrastructure.

About the role

We are looking for a Member of Technical Staff to work across research, engineering, product, and customer-facing technical initiatives.

This is a highly technical, cross-functional role for someone with a strong foundation in artificial intelligence, machine learning, data science, quantitative analysis, and software systems. You will work closely with the founders and technical teams to turn advances in AI and information retrieval into measurable product improvements, customer solutions, evaluation systems, and new technical capabilities.

The role combines hands-on technical problem solving with broad ownership. You may analyze large datasets, design evaluation frameworks, prototype technical solutions, investigate retrieval or model performance, work with customers on complex AI systems, or help drive a new technical initiative from an ambiguous problem to production.

As an early-stage company, responsibilities may span several technical areas depending on the highest-priority problems facing the company.

What you'll do

AI Systems and Technical Product Development

Work with research and engineering teams to develop and improve Mixedbread's AI retrieval and search systems.
Apply machine learning, data science, information retrieval, experimentation, and quantitative methods to technical product problems.
Evaluate developments in information retrieval, embedding models, multimodal search, LLM-based systems, agentic retrieval, and related AI technologies.
Translate research results and technical findings into product capabilities, technical requirements, experiments, and production systems.
Investigate performance, quality, scalability, and reliability issues across AI models, retrieval systems, and supporting infrastructure.
Prototype and evaluate new technical approaches before broader product or infrastructure investment.

Data, Metrics, Experimentation, and Evaluation

Develop quantitative metrics for retrieval quality, model performance, product usage, reliability, latency, and other technical objectives.
Design and implement evaluation frameworks for AI and retrieval systems, including offline benchmarks and real-world customer evaluations.
Analyze large and complex datasets to identify product opportunities, performance bottlenecks, model behavior, customer usage patterns, and areas for technical improvement.
Design experiments and analytical frameworks to evaluate new models, retrieval techniques, system architectures, and product capabilities.
Build tooling and analytical systems that make technical performance measurable and reproducible.
Synthesize experimental results and technical evidence into recommendations for research, engineering, and product decisions.

Technical Projects and Systems

Own technically complex projects spanning research, engineering, infrastructure, product, and customer deployments.
Convert ambiguous technical problems into structured investigations, experiments, prototypes, and production workstreams.
Define technical objectives, evaluation criteria, implementation approaches, and success metrics for new initiatives.
Identify bottlenecks in AI systems, infrastructure, data pipelines, and technical workflows and develop scalable solutions.
Build internal tools, prototypes, analyses, and systems that improve engineering and research execution.
Work closely with engineers and researchers to move promising technical ideas from experimentation into production.

Customer Engineering and Applied AI

Work directly with customers and partners to understand their data environments, retrieval challenges, AI architectures, and technical requirements.
Analyze customer datasets, queries, evaluations, and system behavior to understand retrieval and model performance.
Develop technical solutions and prototypes for integrating Mixedbread's technology into customer AI systems.
Collaborate with research and engineering teams to translate real-world customer problems into improvements to models, APIs, infrastructure, and product capabilities.
Support technically complex deployments and evaluations of Mixedbread's retrieval technology.
Communicate machine learning, retrieval, data, and systems concepts clearly to technical and non-technical stakeholders.

Research and Technical Strategy

Investigate emerging techniques in machine learning, information retrieval, AI infrastructure, agentic systems, multimodal AI, and related areas.
Conduct technical analyses of new model architectures, datasets, benchmarks, infrastructure approaches, and external technologies.
Help identify areas where new research or engineering investments could materially improve Mixedbread's systems.
Support technical decisions with experiments, quantitative analysis, prototypes, and research.
Contribute to technical roadmap discussions with the founders, research team, and engineering team.
Support technical diligence for new technologies, infrastructure investments, partnerships, and product opportunities.

Technical Leadership and Company Building

Take ownership of important technical problems that do not fit cleanly within a single existing team.
Collaborate across research, engineering, product, and customer-facing teams to ensure technical initiatives are executed effectively.
Develop tools, metrics, and technical processes that allow the company to operate effectively as it scales.
Participate in interviewing and evaluating candidates for technical roles.
Help communicate Mixedbread's technology, research, and technical capabilities to customers, partners, candidates, and other stakeholders.

What we're looking for

Bachelor's or advanced degree in Computer Science, Data Science, Computational Engineering, Applied Mathematics, Statistics, Machine Learning, or a closely related quantitative technical field, or equivalent technical experience.
Strong foundation in machine learning, data science, algorithms, statistical analysis, experimentation, or computational methods.
Strong programming ability and experience using software and data tools to investigate and solve technical problems.
Experience working with complex datasets and using quantitative analysis to evaluate systems and inform technical decisions.
Ability to understand complex AI and software systems across multiple layers of the stack.
Experience working closely with engineering, machine learning, research, or data science teams.
Ability to independently structure ambiguous technical problems, develop hypotheses, run experiments, and communicate conclusions.
Strong written and verbal communication skills, including the ability to explain technical concepts across different audiences.
High degree of ownership and comfort operating in a fast-moving early-stage technology company.

Nice to have

Professional experience in machine learning, data science, applied AI, software engineering, research engineering, or another highly technical role.
Graduate-level education in a computational, mathematical, engineering, or data science discipline.
Experience designing experiments, developing quantitative metrics, or building evaluation systems for machine-learning products.
Familiarity with information retrieval, embeddings, vector search, transformers, RAG, LLMs, multimodal AI, or machine-learning infrastructure.
Experience developing or evaluating production AI systems.
Experience working with large-scale consumer or enterprise technology products.
Experience working directly with customers on technically complex AI or data systems.
Experience operating in high-growth startups or other environments requiring rapid technical prioritization and execution.

What success looks like

Building technical systems, analyses, and evaluation frameworks that improve Mixedbread's AI products.
Improving the company's ability to make rigorous, data-informed technical decisions.
Accelerating the development and deployment of new retrieval and AI capabilities.
Translating research advances into measurable improvements in production systems and customer outcomes.
Identifying and solving important technical problems across models, data, infrastructure, product, and customer deployments.
Helping Mixedbread maintain a high level of technical execution as the company and its systems scale.

What We Offer

Competitive compensation + equity
Comprehensive health, dental, and vision coverage
Visa sponsorship + relocation support
Professional development budget
Access to the best AI tools and subscriptions
Team off-sites + conference attendance
Transportation support
Wellness support, including gym membership and sports club subscriptions
Food support

Mixedbread is an equal opportunity employer committed to building a diverse and inclusive team. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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