The Role:

As a Store Manager, you are a charismatic leader with exceptional service and sales acumen. Reporting into the Multi Site Leader you will drive the growth and awareness of Mejuri in your store and market. You are passionate about leading teams and recognize the importance of leading by example, building motivation, and creating an environment that demonstrates the Mejuri values. You are the ultimate ambassador of the Mejuri brand; accountable for creating a highly productive store environment in which we exceed customer expectations, and create an engaging and inclusive environment where employees are motivated and supported to do their best. You reflect and celebrate milestones with your team and are focused on how to continue to grow & develop your team members focused on a high level of engagement. You will manage and provide oversight on all aspects of profit, customer, people, merchandising and operations in your store, partnering with various cross-functionals to exceed targets.

Customer:

• Revenue & Profitability: Responsible for the financial health and profitability of your store, driving revenue and exceeding targets.
• STACK: Lead by example and validate the quality of the in-store customer experience by communicating, training, and upholding expectations on the team on Mejuri’s customer service model.
• STACK Leadership: Maximize results and achievement of Key Performance Indicators (KPIs), by driving own performance as well as the performance and engagement of the team
• Experiences: Ensure positive customer experience and promotion of services offerings including piercing, engraving, and other offerings.
• KPIs: Revenue results, STACK segment success, NPS, CVR, OPH, SPH

Operations:

• Inventory: Partner with Operations teams to hold successful inventory & cycle counts on a monthly basis, ensuring teams have proper technology in place and troubleshooting guidance where needed.
• Order Fulfillment: Manage the back of house flow to support in-store sales, phone sales or BOPIS, ensuring efficiency with packaging and order delivery standards.
• Storage & Organization: Maintain organizational integrity of our BOH up to and including display inventory and sellable inventory, packaging, and all supplies.
• Systems & Technology: Proficient in using point-of-sale systems, inventory management software, and other retail technology.
• Supplies: Maintain organizational integrity of our BOH up to and including store supplies such as display inventory, sellable inventory and packaging.
• Shrink: Accountable for mitigating internal, external and administrative loss of product.
• Escalations: Identify and escalate opportunities, gaps, risks and roadblocks with urgency and partner as needed with cross functional teams to resolve.
• KPIs: Shrink, EBITDA,  IS Receiving Time (24 Hours), Time to Pack, Inventory Accuracy

Merchandising:

• Merchandising: Ensure Mejuri brand standards of visual presentation, cleanliness and functionality
• Assortment & Replenishment: Monitor assortment performance to create a productive sales environment and determine action steps to improve sell-through
• Campaigns: Oversee implementation and maintenance of all retail campaign signage and windows in your location.
• Fixtures & Maintenance: Validate the integrity of all display forms, graphics, furniture, and decor items to manage costs and propel the brand, notifying appropriate teams when display tools are missing or damaged.
• Visual Standards: Coach and inform all store team members on updates or changes to Visual Merchandising standard practices.
• Escalations: Flag, identify and action any inefficiencies
• KPIs: Sku Representation, Flagship Visual Execution (Timeliness & Accuracy)

People:

• Planning: Ensure that we have the right people in the right positions at the right time and in the right quantities across your stores
• Hiring: Own the sourcing, assessment, and selection of talent to build the infrastructure necessary to sustain and grow your business
• Onboarding: Validate and participate in the successful integration of new talent to our store teams.
• Training: Validate that team members are completing required instructor-led, on the job and self study trainings.
• Scheduling: Ensure that store schedules are supported with high quality and accurate inputs and uphold the standards of responsible live-week management
• Assessing: Validate the regular and accurate assessment of our people against performance review criteria and KPIs.
• Engaging: Build healthy relationships with our people and establish a positive and engaging work environment.
• Employee Relations: Adhere to and validate our compliance practices and partner with People Operations to resolve escalations as they arise
• KPIs: Vacancy Rate, Employee Engagement, Turnover , Training Completion Compliance

What you'll bring to the team:

• Experience in high-volume retail environment.
• Understanding of local market and requirements relevant to new store openings.
• Financial management experience with success in driving top-line sales, interpreting reporting data, managing payroll budgets, and controlling expenses.
• Exceptional leadership capabilities with a track record of attracting, developing, and motivating top talent, swiftly adapting to change, and leading others through the fast paced environments.
• Demonstrated understanding of service excellence in a consumer environment.
• Excellent communication skills.
• Deep local knowledge and informed of trends in retail, you’re well connected, and you know how to navigate and grow your network to get the introductions you need.
• Desire to work in a fast paced, entrepreneurial environment–you understand the importance of experimentation and iteration.
• Bonus: You have opened a store from scratch.
• Bonus: You have worked at a start-up or fast growing company.

Benefits at Mejuri:

• US & CA ONLY: Comprehensive medical, dental, and mental health coverage, designed with flexibility, inclusivity & reproductive health in mind.
• US ONLY: Opportunity to utilize 401(k) & commuter benefits plans.
• UK ONLY: Comprehensive medical benefits including PMI, Cashplan, and Pension program
• Paid time off – inclusive of vacation and sick days.
• 4 months of 80% parental leave salary top-up and personalized return to work plans.
• Monthly retail bonus program.
• Equity program – own a piece of the company and share in our growth.
• Regular feedback via performance reviews.
• A robust in-house retail learning program
• Generous product discount!

#LI-Onsite

Looking for the perfect next opportunity is a big decision. Mejuri recognizes the importance of pay transparency when it comes to salary ranges as it empowers individuals through the hiring process and supports them in making an informed decision. This role currently has a base pay range of $85,000 - $100,000 per annum based on a candidate’s experience and qualifications.

The Role:

A Stylist at Mejuri is more than a salesperson—it’s a pivotal role in delivering an exceptional, personalized shopping experience that embodies our commitment to redefining luxury. As a trusted advisor to every customer, the Retail Stylist bridges the gap between beautiful jewelry and meaningful moments, ensuring every interaction reflects Mejuri’s core values and dedication to excellence.

Our Stylists create a warm, welcoming environment where customers feel valued and empowered to make confident choices. Through expert product knowledge, a deep understanding of style, and a passion for storytelling, you’ll guide customers in discovering pieces that resonate personally while driving key performance metrics such as sales, conversion, and customer satisfaction.

Stylists at Mejuri are engaging, nimble, creative and driven. Join us in redefining luxury—one customer, one team member, and one exceptional experience at a time.

Customer:

• STACK: Lead by example and validate the quality of the in-store customer experience by communicating, training, and upholding expectations on the team on Mejuri’s Steps of Selling.
• Services: Ensure positive customer experience and promotion of services offerings including piercing, engraving, and other offerings.
• KPIs: OPH, SPH, NPS (85%<)

Operations:

• Order Fulfillment: Participate as needed the back of house flow to support in-store sales, phone sales or BOPIS, ensuring efficiency with packaging and order delivery standards.
• Storage & Organization: Support in maintaining organizational integrity of our BOH up to and including display inventory and sellable inventory, packaging, and all supplies.
• Systems & Technology: Experience using or possesses the ****ability to learn to use point-of-sale systems and other retail technology.
• Shrink: Supports in mitigating internal, external and administrative loss of product.
• Escalations: Participate in Identify and escalate opportunities, gaps, risks and roadblocks to store leadership.

Merchandising:

• Merchandising. Support in ensuring that Mejuri brand standards of visual presentation, cleanliness and functionality are upheld
• Fixtures & Maintenance. Support with validating the integrity of all display forms, graphics, furniture, and decor items to manage costs and propel the brand, notifying appropriate teams when display tools are missing or damaged.
• Escalations: Flag, identify and action any inefficiencies

People:

• Engaging: Build healthy relationships with our people and establish a positive and engaging work environment.
• Employee Relations: Adhere to our policies compliance practices.

What you'll bring to the team:

• An ability to connect with all of our customers in an authentic and warm way that makes them feel comfortable and keeps them coming back.
• Strong verbal communication skills and active listening to effectively deliver on our customer needs and work as a team.
• An ability to learn and retain relevant product knowledge to suggest and style for our customers.
• Is able to think critically and solution in the moment to deliver on customer and business needs effectively.
• An ability to meet and exceed key performance indicators including SPH, Conversion, NPS, AOV, UPT.
• Ability to pay attention to customer feedback, trends and shares insights with management.
• Great attention to detail, and a highly organized working style and strong sense of initiative.
• Ability to work on the sales floor for extended periods of time.
• History of successfully participating in and contributing to a positive team working environment.

Benefits at Mejuri:

• Paid sick days.
• Monthly retail bonus program.
• Regular feedback via performance reviews.
• A robust in-house retail learning program
• Generous product discount!

#LI-Onsite

Looking for the perfect next opportunity is a big decision. Mejuri recognizes the importance of pay transparency when it comes to salary ranges as it empowers individuals through the hiring process and supports them in making an informed decision. This role currently has a base pay range of $19- $20 per hour based on a candidate’s experience and qualifications.

Job Title: Senior Applied AI/ML Scientist (Deep Learning and Generative Models)

Company Overview: Kindo is an agent automation platform for DevOps and SecOps teams. We help organizations automate high-friction operational work using autonomous agents that run in the background — reliably, securely, and at scale.

We're ~40 people with strong customer traction, real enterprise revenue, and the infrastructure to support serious AI development. This isn't a side bet on AI. It's the entire company.

At the heart of our platform is DeepHat, Kindo's uncensored cybersecurity model. Built for real offensive reasoning, long-context analysis, and secure execution, DeepHat serves as the "AI Brain" of our platform. It is trained on real-world attack patterns and high-signal security data to power precise, autonomous workflows. As a member of the DeepHat team, you will be responsible for pushing the boundaries of what specialized LLMs can achieve in the realm of digital defense.

Job Description:

We are seeking a highly experienced Senior Applied AI/ML Scientist with a specialization in deep learning and generative models to join our dynamic team. In this role, you will play a pivotal part in the architecture and implementation of our AI modeling efforts, with a specific focus on post-training and fine-tuning large language models.

While this role requires deep technical expertise, we value a collaborative environment where good ideas flourish regardless of title. You will work within a team that empowers engineers to own their stack end-to-end. The ideal candidate has strong AI/ML fundamentals and can bridge the gap between theoretical research and practical production systems. You should be comfortable working with Agentic LLM usage and modern fine-tuning approaches, ranging from Supervised Fine-Tuning to Knowledge Distillation to RL, to create robust, reliable enterprise solutions.

You will be an early engineer at a high-growth startup, playing a significant role in building and bringing a new generative AI product to market. We are looking for a systems-thinker who cares as much about model evaluation and production stability as they do about algorithmic innovation.

Responsibilities:

• Rigorous Evaluation (Evals): Architect, build, and maintain comprehensive evaluation pipelines. You believe that "you can't improve what you don't measure," and you will be responsible for creating evals that accurately reflect production performance and agentic reliability.
• Post-Training & Fine-Tuning: Apply expert knowledge of model alignment and post-training strategies to tailor our in-house LLMs for enterprise capabilities. You should be adept at selecting and implementing the right technique for the job. Whether that is Supervised Fine-Tuning (SFT), Knowledge Distillation, PEFT, or leveraging alignment methods like Reinforcement Learning from Verifiable Rewards (RLVR) when appropriate.
• Hands-on Data Engineering & Strategy: Go beyond just "using" data. You will be responsible for the end-to-end data lifecycle—sourcing, cleaning, curating, and modifying datasets to maximize model effectiveness and domain specificity.
• Training & Inference Optimization: Utilize and optimize the open-source LLM ecosystem for the full model lifecycle. You will leverage distributed training tools (e.g., Accelerate, DeepSpeed/FSDP) and high-throughput serving engines (e.g., vLLM, TensorRT-LLM) to ensure efficiency from training to production.
• End-to-End Ownership: Take a systems-level approach to AI. You will not just build models in isolation but will be responsible for the E2E lifecycle of the model, including how it integrates into production and interacts with the broader application.
• Collaboration & Mentorship: Work closely with cross-functional teams to translate product requirements into technical AI solutions. While this is an individual contributor role, you will be expected to mentor junior members, review code, and contribute to a culture where technical ideas are debated openly and constructively.

Required Qualifications:

• Education: PhD or MS in Computer Science, Machine Learning, AI, or a related field, or equivalent practical experience.
• Experience: 3-5+ years of experience in AI/ML with a strong focus on deep learning, generative models, and LLMs.
• Effective AI Collaboration: You don't just "use" AI tools (e.g. Cursor, Claude Code, Devin, etc.); you know how to effectively partner with them to drive real efficiency. You know how to thoughtfully prompt, delegate, and iterate with these AI to achieve concrete productivity gains and genuinely accelerate your development process.
• Evaluation Expertise: Demonstrated experience designing metrics and building evaluation harnesses for non-deterministic models. You understand that robust evals are the cornerstone of successful AI products.
• Fine-Tuning Expertise: Deep understanding of the post-training landscape, with practical experience in techniques such as SFT, PEFT (LoRA/QLoRA), and Knowledge Distillation.
• Applied Frameworks: Proficiency with the modern open-source LLM ecosystem. Experience with distributed training (e.g., Accelerate, FSDP, DeepSpeed) and high-level modeling libraries.
• Strong Fundamentals: Deep conceptual understanding of the mathematical and architectural underpinnings of AI/ML (gradients, attention mechanisms, loss landscapes). While we don't code in raw TensorFlow/PyTorch daily, we value the first-principles understanding that comes with knowing these layers.
• Systems Engineering: Experience with software engineering best practices and an ability to write clean, production-ready code. You should be comfortable with the "Ops" side of MLOps.
• Problem Solving: Strong critical thinking skills with a pragmatic focus on shipping solutions that work for users, not just maximizing academic benchmarks.
• Location: Hybrid Onsite in Venice, CA (2 days a week).

Preferred Qualifications:

• LLM Production Experience: Practical experience deploying and maintaining LLMs in a production environment.
• Advanced Alignment: Familiarity with emerging alignment research (e.g., DPO, RLVR) and an ability to determine when these complex methods add value over simpler baselines.
• Agentic Concepts: Strong conceptual understanding of Agentic architectures (planning, tool use, ReAct loops, etc.). 
• Enterprise Context: Knowledge of enterprise security best practices and experience with Enterprise SaaS software.
• Research Impact: A track record of staying current with arXiv papers and successfully translating a research concept into a working feature.

What We Offer:

• Competitive salary (Range: $170k-$220k Base) and Equity
• Comprehensive health, dental, and vision insurance
• Unlimited vacation and paid time off policies
• A chance to be part of a groundbreaking company shaping the future of generative AI

Company Culture:

• Start-up and entrepreneurial mindset: High-energy, passionate, and willing to put in a bit of extra energy to ensure we succeed, but mindful of work-life balance, protecting weekends, and accommodating personal obligations. Full belief in the multi-billion dollar market opportunity in front of us.
• Strong ownership culture: Complete ownership of core areas of responsibility, but also welcoming ideas and contributions from everyone. Everyone acts like product owners and contributes where they can provide value.
• Fast-paced and action-oriented: Focus on high velocity, minimal processes, and utilizing existing solutions to maximize product development and minimize maintenance overhead. Focused on outcomes over hours. We work smarter, not harder.
• Empathy, open-mindedness, and constructive feedback: Respect diverse working styles, encourage data-informed decisions, and build understanding and trust through direct conflict resolution
• Reflective thinking and effectiveness: Balance thoughtful planning and discipline with action, prioritize finding solutions that meet customer needs over being right
• Collaboration and support: Foster an environment where employees can work together, rely on each other, and support one another through challenges

If you are a passionate and talented AI researcher looking to make a meaningful impact in the generative AI space applied into end-user products, we would love to hear from you. Apply now and join our team of visionaries in creating the next unicorn company in the AI industry.

Principal AI Systems Engineer — Agentic Platforms

The Moment

The role of the software engineer is changing. Autonomous agents can now execute real workflows, operate infrastructure, and improve over time. The hard problems are shifting from model demos to production systems: orchestration, memory, reliability, control, and security.

OpenAI acquired OpenClaw. Meta paid $2B for Manus. The agent platform layer is becoming one of the most important layers in the stack.

At Kindo, we’re already there. Our platform runs autonomous agents in production at real enterprises, automating DevOps and SecOps workflows with real permissions, real consequences, and real reliability requirements.

About Kindo

Kindo is an agent automation platform for DevOps and SecOps teams. We help organizations automate high-friction operational work using autonomous agents that run reliably, securely, and at scale. Our platform supports deployment on-prem, in hybrid environments, or in the cloud, with enterprise-grade security controls from day one.

We’re a small, highly technical team with strong customer traction and real enterprise revenue. Engineers have direct ownership over critical systems and shape the platform’s technical direction and long-term evolution.

The Role

You will define and evolve the architectural foundations of Kindo’s agent platform. This is applied systems engineering at the frontier of AI-native development, not ML research and not chatbot wrappers. You’ll work on agent execution frameworks, memory architectures, multi-model execution, secure tool-calling integrations, and the platform primitives that determine what autonomous systems can reliably do.

This role requires invention and unusually strong technical judgment. Many of the paradigms for agentic systems are still emerging. You’ll continuously track the ecosystem, explore new approaches, prototype quickly, and decide what becomes the platform’s durable foundation. You will identify the highest-leverage architectural opportunities, the failure modes most likely to bite us, and the guardrails and abstractions that let the system scale safely.

Principal engineers at Kindo are builders and inventors who help determine what the future of agentic systems should look like, while ensuring the platform remains reliable, secure, observable, debuggable, and maintainable under real-world conditions.

What You’ll Build

• Agent execution architectures, including autonomous task loops, scheduling, triggers, control planes, and failure isolation
• Retrieval and memory architectures, including persistent, structured, and contextual memory systems
• Multi-model routing and orchestration across providers, balancing quality, latency, cost, and failure modes
• Tool-calling and integration frameworks for safe interaction with external services and enterprise environments
• Reliability, security, and operability foundations, including evaluation, observability, auditing, and recovery paths
• Core platform primitives and architectural patterns that enable entirely new autonomous capabilities safely

How You Build

AI is a first-class tool in how we engineer. You use AI across design, prototyping, implementation, testing, debugging, and incident response, and you continuously refine workflows that increase leverage without sacrificing quality. At this level, you also help define the engineering paradigm itself: how we use autonomous agents and AI-driven workflows to compound velocity over time while minimizing slop, security risk, and architectural drift.

You build with discipline. You create boundaries, verification strategies, and operational guardrails so systems remain understandable and controllable as autonomy increases. You ensure the platform can evolve rapidly without losing reliability and security.

What We’re Looking For

We care far more about what you’ve built than what’s on your resume.

You:

• Have deep expertise designing and operating complex backend or distributed systems in production
• Have built and evolved platform-level architectures that remained durable under rapid change
• Have built LLM-powered or AI-native systems beyond demos, with real users, constraints, and failure modes
• Demonstrate exceptional architectural judgment around reliability, security, observability, and long-term system evolution
• Have invented or introduced foundational abstractions, workflows, or architectural approaches that materially improved system capability or engineering effectiveness
• Actively track emerging tools, models, and approaches and translate the best of them into production systems
• Use AI as a core part of your engineering workflow, not as an occasional convenience
• Operate with exceptional ownership and take systems end-to-end, including long-term evolution

Technical requirements:

• TypeScript required, Python strongly preferred
• Strong SQL proficiency
• Experience with production infrastructure; Docker/Kubernetes experience is a plus
• Familiarity with enterprise security patterns is a plus
• Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus

Culture

Small team, high autonomy, high ownership. We move fast, prototype aggressively, and ship what works. We maintain high standards around reliability, security, and clarity. We value builders, explorers, and inventors who want to help define the future of agentic systems.

Compensation and Location

Compensation: $250,000–$330,000 base salary plus competitive equity
Location: Venice, San Francisco, Remote, or Hybrid

How to Apply

Send us:

• Your work. A portfolio, demo, GitHub profile, blog post, recorded walkthrough, or any evidence of AI systems you’ve built. We want to see how you think, not just what you’ve done.
• A brief note on what excites you about agentic systems and where you think the hard problems are.
• Your resume, but know that the first two items matter more.

We’ll move fast. The interview process is designed to see how you actually work, not quiz you on trivia.

Staff AI Systems Engineer — Agentic Platforms

The Moment

The role of the software engineer is changing. Autonomous agents can now execute real workflows, operate infrastructure, and improve over time. The hard problems are shifting from model demos to production systems: orchestration, memory, reliability, control, and security.

OpenAI acquired OpenClaw. Meta paid $2B for Manus. The agent platform layer is becoming one of the most important layers in the stack.

At Kindo, we’re already there. Our platform runs autonomous agents in production at real enterprises, automating DevOps and SecOps workflows with real permissions, real consequences, and real reliability requirements.

About Kindo

Kindo is an agent automation platform for DevOps and SecOps teams. We help organizations automate high-friction operational work using autonomous agents that run reliably, securely, and at scale. Our platform supports deployment on-prem, in hybrid environments, or in the cloud, with enterprise-grade security controls from day one.

We’re a small, highly technical team with strong customer traction and real enterprise revenue. Engineers have direct ownership over critical systems and shape how the platform evolves.

The Role

You will define, build, and evolve foundational systems that enable autonomous agents to operate reliably in production. This is applied systems engineering with AI at the center, not ML research and not chatbot wrappers. You’ll work on agent execution frameworks, retrieval and memory systems, multi-model execution, and secure tool-calling integrations that interact with real enterprise environments.

This role also requires invention. Many of the patterns for agentic systems are still emerging. You’ll explore new approaches, prototype quickly, and turn what works into durable platform foundations. You’ll identify high-leverage architectural improvements, abstractions, and guardrails that expand what the platform can do while keeping it reliable, secure, observable, and maintainable under real-world conditions.

Staff engineers at Kindo are builders and inventors with strong architectural judgment. You help define both what we build next and which approaches become the system’s durable defaults.

What You’ll Build

• Agent execution systems, including autonomous task loops, scheduling, triggers, and control planes
• Retrieval and memory architectures, including context management, long-term memory, and structured memory
• Multi-model routing and orchestration across providers, balancing quality, latency, cost, and failure modes
• Tool-calling and integration frameworks for safe interaction with external services and enterprise environments
• Reliability, security, and operability foundations, including evaluation, observability, failure isolation, and recovery paths
• Core platform abstractions and architectural patterns that make new agent capabilities easier to build safely

How You Build

AI is a first-class tool in how we engineer. You use AI across design, prototyping, implementation, testing, debugging, and incident response, and you continuously refine workflows that increase leverage without sacrificing quality. You develop pragmatic guardrails, verification strategies, and architectural boundaries to minimize slop, reduce risk, and keep systems safe as autonomy increases.

You also push the team’s defaults forward through better patterns, reusable workflows, and clearer architectural primitives, so the whole organization builds faster with fewer failure modes.

What We’re Looking For

We care far more about what you’ve built than what’s on your resume.

You:

• Have deep experience building and operating complex backend or distributed systems in production
• Have built LLM-powered or AI-native systems beyond demos, with real users, real constraints, and real failure modes
• Have strong architectural judgment around reliability, security, observability, and system evolution
• Have invented or introduced abstractions, workflows, or architectural approaches that materially improved system capability or engineering effectiveness
• Are comfortable operating in ambiguous frontier areas and validating ideas through rapid iteration
• Use AI as a core part of your development workflow, not as an occasional convenience
• Operate with high ownership and take systems end-to-end, including long-term evolution

Technical requirements:

• TypeScript required, Python strongly preferred
• Strong SQL proficiency
• Experience with production infrastructure; Docker/Kubernetes experience is a plus
• Familiarity with enterprise security patterns is a plus
• Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus

Culture

Small team, high autonomy, high ownership. We move fast, prototype aggressively, and ship what works. We maintain high standards around reliability, security, and clarity. We value builders, explorers, and inventors who want to help define the future of agentic systems.

Compensation and Location

Compensation: $210,000–$260,000 base salary plus competitive equity
Location: Venice, San Francisco, Remote, or Hybrid

How to Apply

Send us:

• Your work. A portfolio, demo, GitHub profile, blog post, recorded walkthrough, or any evidence of AI systems you’ve built. We want to see how you think, not just what you’ve done.
• A brief note on what excites you about agentic systems and where you think the hard problems are.
• Your resume, but know that the first two items matter more.

We’ll move fast. The interview process is designed to see how you actually work, not quiz you on trivia.