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# Member of Technical Staff (Applied AI)

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/reka.md)Share7 Sep 2026Published43Listing views3Application actions7 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryThis is a senior, customer-facing applied AI engineering role focused on productionizing frontier multimodal models for practical business problems. The Member of Technical Staff will collaborate with research peers, integrate models into customer technology stacks, and retain substantial product ownership. The role seeks hands-on machine learning engineering experience, particularly with transformers and LLMs, plus comfort operating amid startup ambiguity. It is positioned as a founding-team opportunity in a globally distributed, remote-first foundation-model company.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThe position requires deep practical ML expertise alongside the ability to deploy frontier models reliably in customer environments. Founding-team scope, ambiguous problems, and direct customer integration create a high bar for technical judgment, ownership, and adaptability.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$220,000US market range$170k–$300k0$330k

AI insightNo salary, base-pay range, or other role-payment amount is disclosed. This is an estimated US annual base-salary market range in USD for a senior Applied AI/ML Member of Technical Staff at a frontier-model startup; actual compensation may vary substantially by level, location, equity, and cash-versus-equity mix.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Applied AI](https://jobicy.com/jobs?search_keywords=Applied%20AI.md)[Machine Learning Engineering](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Engineering.md)[Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[Transformer Models](https://jobicy.com/jobs?search_keywords=Transformer%20Models.md)[Multimodal AI](https://jobicy.com/jobs?search_keywords=Multimodal%20AI.md)[Model Productionization](https://jobicy.com/jobs?search_keywords=Model%20Productionization.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[Customer Integration](https://jobicy.com/jobs?search_keywords=Customer%20Integration.md)[Cross-Functional Collaboration](https://jobicy.com/jobs?search_keywords=Cross-Functional%20Collaboration.md)

Sample interview questionsDescribe an AI or ML system you took from prototype to production. What were the key engineering decisions?I would explain the problem, model-selection rationale, data and evaluation strategy, serving architecture, monitoring, and rollout plan. I would emphasize measurable outcomes, reliability safeguards, and how production feedback informed iterative model improvements.

How would you evaluate whether a frontier LLM or multimodal model is suitable for a customer use case?

I would begin with the customer's workflow, risk tolerance, success metrics, and data constraints. I would create representative evaluation sets, compare quality, latency, cost, safety, and robustness across candidate approaches, then recommend a staged pilot with clear acceptance criteria.

How do you manage ambiguity when requirements are incomplete and the technical path is uncertain?

I turn ambiguity into explicit hypotheses, identify the highest-risk assumptions, and run small experiments to reduce uncertainty quickly. I communicate trade-offs early, align stakeholders on decision criteria, and maintain momentum through short, measurable milestones.

What challenges have you encountered when integrating ML models into a customer's existing technology stack?

Common issues include data quality, authentication, latency expectations, deployment constraints, observability, and differing interpretations of model behavior. I address these through early architecture discovery, well-defined interfaces, secure integration patterns, instrumentation, and joint testing with the customer team.

How do you collaborate effectively with researchers while ensuring models become useful products?

I translate product and customer needs into measurable technical requirements while preserving a tight feedback loop with researchers. I share production findings such as failure modes, evaluation results, and operational constraints so research priorities and engineering implementation improve each other.

As a Member of Technical Staff on Applied AI, you will:

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Productionize frontier AI models to solve complex real-world problems.

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Collaborate closely with researchers and other teammates on the latest advancements in AI and ML.

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Work closely with our customers to integrate our models into their technology stack.

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Make direct business impact with a high level of product ownership.

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Be a founding member of a fast-growing team and wear many hats.

You may be a good fit, if you have:

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An obsession with customers and a passion for solving practical (but sometimes ambiguous) real-world problems.

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Experience as a machine learning engineer, ideally working on AI products for external customers.

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Background as a technical founder or in a similar capacity.

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Practical experience working with transformer models and LLMs.

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An exceptional ability to communicate and work effectively with cross-functional teams.

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Track records of owning problems end-to-end, and can learn fast and pick up new knowledge to get the job done.

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A kind and collaborative nature and work style.

Reka’s Mission

Reka’s mission is to build useful multimodal artificial intelligence and use it to empower organisations and businesses. We are a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world. Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade.

Why Reka?

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An Elite Team: Collaborate with top-tier engineers, researchers, operators from renowned organizations like Google DeepMind and Facebook AI Research (FAIR) and successful startups, driving innovation in cutting-edge AI technology.

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Massive Market Opportunity: Be part of a rapidly growing industry poised to transform multiple sectors globally, offering the chance to make a significant impact.

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Mission-Driven Environment: Work alongside a collaborative, mission-focused team dedicated to advancing AI for meaningful applications.

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Inclusive and Open Culture: Thrive in an open and inclusive work environment that values diverse perspectives and fosters creativity.

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Generous Benefits: Enjoy 5 weeks of paid leave to recharge, comprehensive healthcare benefits including vision and dental, and additional perks that support your well-being.

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Visa Support: We provide visa assistance, including H1B and OPT transfers, for US employees to ensure a smooth transition and support your career with us.

Show more

[Apply now >](https://jobicy.com/jobs/152763-member-of-technical-staff-applied-ai.md)

>  Annual salary information is not provided for this position. Explore salary ranges for similar roles in our [Salary Directory ›](https://jobicy.com/salaries.md)

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