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# Member of Technical Staff (ML)

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 2026Published27Listing views1Application actions7 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryReka is hiring a Machine Learning Member of Technical Staff to develop large, multimodal deep-learning models across the full model-development lifecycle. The role covers dataset preparation, architecture design, implementation, distributed training, evaluation, and product-focused model improvement. It requires strong practical experience with large-scale ML systems and frameworks such as PyTorch or JAX. The position is suited to an adaptable engineer-researcher who can work autonomously in a fast-moving foundation-model startup while collaborating closely with researchers and engineers.

## 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

4/5IndependentCollaborative

AI insightThis is a highly technical role involving large-model training and production implementation, requiring both deep-learning expertise and the ability to translate research into scalable software. Startup ambiguity, broad ownership, and cutting-edge multimodal AI work raise the complexity further.

## Salary analysis

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

Estimated job medianMarket rate$220,000US market range$180k–$280k0$308k

AI insightNo salary or pay range is disclosed in the posting. This is an estimated US annual base-salary market range for a highly skilled ML Member of Technical Staff working on large-scale foundation models; total compensation may be higher depending on equity, bonus, location, and level.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Deep Learning](https://jobicy.com/jobs?search_keywords=Deep%20Learning.md)[Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[Multimodal AI](https://jobicy.com/jobs?search_keywords=Multimodal%20AI.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[JAX](https://jobicy.com/jobs?search_keywords=JAX.md)[Model Training](https://jobicy.com/jobs?search_keywords=Model%20Training.md)[Model Evaluation](https://jobicy.com/jobs?search_keywords=Model%20Evaluation.md)[Data Preparation](https://jobicy.com/jobs?search_keywords=Data%20Preparation.md)[Scalable ML Systems](https://jobicy.com/jobs?search_keywords=Scalable%20ML%20Systems.md)

Sample interview questionsDescribe a large deep-learning model you trained or fine-tuned and the most important technical trade-offs you made.I would outline the model architecture, dataset scale and quality controls, compute environment, and evaluation goals. I would then explain trade-offs such as model size versus latency or cost, data diversity versus noise, and training stability versus throughput, supported by measured outcomes.

How would you diagnose unstable or diverging training for a large neural network?

I would first validate data integrity, preprocessing, labels, and batching, then inspect loss curves, gradient norms, activations, and optimizer state. I would test learning-rate schedules, precision settings, normalization, gradient clipping, initialization, and distributed-training configuration through controlled experiments.

How do you translate a promising research result into a dependable software feature?

I begin by defining product metrics, constraints, and failure modes, then reproduce the result with versioned data and experiments. I build robust evaluation and monitoring, optimize serving behavior, document assumptions, and partner with engineering teams to deploy and iterate safely.

What evaluation approach would you use for a multimodal model?

I would combine benchmark performance with task-specific offline evaluation, qualitative error analysis, robustness testing, and safety checks. The evaluation set should represent real user scenarios, include difficult edge cases, and use clear success metrics that can be monitored after release.

How do you operate effectively when requirements are incomplete or changing?

I clarify the highest-impact decision to make, state assumptions explicitly, and propose a small experiment or prototype that reduces uncertainty quickly. I communicate results and risks early, update priorities with stakeholders, and maintain enough documentation for the team to build on the work.

As a Member of Technical Staff on Machine Learning, you will:

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Contribute to the entire development cycle of our cutting-edge large deep learning models.

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Prepare datasets, design architectures, implement solutions, train and evaluate models to improve our products.

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Collaborate closely with engineers and researchers to translate cutting-edge research into practical applications.

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Join us at an exciting moment, wear many hats and help us build something from the ground up!

You may be a good fit, if you have:

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Experience with training and evaluating large deep learning models.

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Proficiency in standard deep learning frameworks (e.g. PyTorch, JAX).

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Proven track record of applying and implementing machine learning algorithms into software applications at scale.

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The ability to build in a fast-paced environment under some uncertainty.

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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/152760-member-of-technical-staff-ml.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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