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Applied AI Engineer, DevOps - Palo Alto

About Mistral


At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.


We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.


We are a dynamic, collaborative team passionate about AI and its potential to transform society.

Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.


Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.


About The Job


Mistral AI is seeking an Applied AI Engineer focused on DevOps to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.


Applied AI Engineers, DevOps at Mistral AI work directly with customers to quickly understand their greatest challenges and design and implement AI solutions. In this role, you’ll apply your problem-solving ability, creativity, and technical skills to help organizations use AI to drive real impact in the world. You’ll have the opportunity to gain rare insight into and contribute to some of the most important industries and institutions globally!


Applied AI Engineers, DevOps responsibilities look similar to those of a startup CTO: you’ll work in small teams and own end-to-end execution of high-stakes projects. A day might span discussing architecture with fellow engineers, wrangling massive-scale data, coding a custom web app, speaking with customer executives, or establishing a strategy for the Applied Engineering team.


What you will do


• You’ll be responsible for onboarding customers on our products, providing guidance on deployment and integration, and ensuring the best production setup from the low-level GPU stack up to infrastructure, back-end and front-end interfaces.

• You’ll work on deploying state-of-the-art AI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.

• You’ll work in collaboration with our researchers, other AI engineers, and product engineers on our most complex customer projects involving deployment, scaling, and contributing to our open-source codebases for tasks such as inference and fine-tuning.

• You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders.


About you


• You are fluent in English

• You hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field

• You have 2+ years of experience in a DevOps or Site Reliability Engineering role

• You're experienced with deploying and managing AI-based products in production environments

• You are fluent in Python

• You have experience with containerization technologies such as Docker and Kubernetes

• You have experience with CI/CD pipelines and automated deployment tools

• You have deep understanding of cloud platforms (AWS, Azure, GCP) and on-premises infrastructure

• You are experienced with infrastructure as code (IaC) tools such as Terraform or Ansible

• You hold strong communication skills with an ability to explain complex technical concepts in simple terms to technical and non-technical audiences


Ideally you have:


• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager

• Familiarity with AI frameworks such as PyTorch or TensorFlow

• Contributions to open-source projects, particularly in the space of DevOps or AI



Benefits


France


💰 Competitive cash salary and equity

🥕 Food : Daily lunch vouchers

🥎 Sport : Monthly contribution to a Gympass subscription 

🚴 Transportation : Monthly contribution to a mobility pass

🧑‍⚕️ Health : Full health insurance for you and your family

🍼 Parental : Generous parental leave policy

🌎 Visa sponsorship


USA


💰 Competitive salary and bonus structure 

🚀 Generous Equity

🧑‍⚕️ Health : Competitive Healthcare program (Medical Provider: Blueshield of California 100% coverage for employee, 75% for dependents)

👴🏻 Pension : 401K (6% matching)

🏝️ PTO : 18 days 

🚗 Transportation: Reimburse office parking charges, or $120/month for public transport

🤝 Coaching: we offer Betterup coaching on a voluntary basis

🏀 Sport: $120/month reimbursement for gym membership

🥕 Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)

🌎 Visa sponsorship 


UK


💰 Competitive cash salary and equity

🚑 Insurance

🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport

🥎 Sport: 90GBP/month reimbursement for gym membership

🥕 Meal voucher: £200 monthly allowance for its meals

💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)


Singapore


Early days in Singapore, in the process of building


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Average salary estimate

$135000 / YEARLY (est.)
min
max
$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Applied AI Engineer, DevOps - Palo Alto, Mistral AI

At Mistral AI, we’re excited to invite an Applied AI Engineer focused on DevOps to join our dynamic team in Palo Alto! We’re all about harnessing the power of AI to simplify tasks and enhance creativity, making it thrive seamlessly in everyday work life. As an Applied AI Engineer, you’ll dive deep into understanding our customers' needs, and help them navigate the complexities of AI integration into their operations. Your role will be unique, reminiscent of a startup CTO, where you'll not only design but ensure the implementation of AI solutions that truly make a difference to companies in various industries. From finding elegant solutions to massive-scale data challenges, working with state-of-the-art applications, to collaborating with our research and product teams, no day will be the same! You’ll guide customers through in-depth onboarding processes, enriching their knowledge about our innovative products while ensuring smooth deployment setups. And with your expertise in tools like Docker and Kubernetes, you'll be pivotal in driving a significant technological transformation alongside our clients! This is your chance to make an impact in the world of AI and work alongside a passionate and creative team that values collaboration and innovation. So, if you have a knack for problem-solving, a background in DevOps, and a desire to contribute to pioneering advancements, we can’t wait for you to join us at Mistral AI!

Frequently Asked Questions (FAQs) for Applied AI Engineer, DevOps - Palo Alto Role at Mistral AI
What are the main responsibilities of an Applied AI Engineer, DevOps at Mistral AI?

As an Applied AI Engineer, DevOps at Mistral AI, you will be responsible for onboarding customers with our AI products, guiding them on deployment and integration, and ensuring best practices for production setups. Furthermore, you will work closely with customers on deploying AI applications, address their technical challenges, and contribute to significant industrial transformations.

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What qualifications do I need to become an Applied AI Engineer, DevOps at Mistral AI?

To become an Applied AI Engineer, DevOps at Mistral AI, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field. You also need a minimum of 2 years' experience in a DevOps or Site Reliability Engineering role, along with expertise in Python, containerization technologies like Docker and Kubernetes, and familiarity with cloud platforms.

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What skills are essential for the Applied AI Engineer, DevOps role at Mistral AI?

Key skills for the Applied AI Engineer, DevOps role at Mistral AI include experience in deploying AI products in production environments, strong communication abilities to convey complex concepts simply, and proficiency in infrastructure as code tools. Additionally, familiarity with AI frameworks, CI/CD pipelines, and cloud infrastructure is highly valuable.

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How does Mistral AI support the professional development of an Applied AI Engineer?

Mistral AI values professional growth and offers supportive measures for Applied AI Engineers, including access to coaching programs like Betterup, participation in community activities, and opportunities for working alongside peers on complex projects that enhance your skills in AI and DevOps.

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What makes Mistral AI a unique workplace for Applied AI Engineers?

Mistral AI stands out as a unique workplace due to its creative, collaborative environment. Our diverse, international team is dedicated to innovation, and the shared passion for AI drives teamwork and culture. You'll find opportunities to work on groundbreaking projects and make a tangible impact while being supported by a company that values its employees.

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Common Interview Questions for Applied AI Engineer, DevOps - Palo Alto
Can you describe a successful AI project you worked on in your previous role?

When discussing a successful AI project, illustrate the challenge you faced, the approach you took, and the outcome. Highlight your role in terms of both technical and collaborative efforts, and how you engaged with different stakeholders to ensure project success.

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How do you manage deployment processes for AI applications?

To manage deployment processes, you should emphasize the tools you use, such as Docker or Kubernetes, and your experience with continuous integration and delivery. Describe your step-by-step approach to ensure a smooth deployment while addressing any potential issues proactively.

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What experience do you have with customer interactions and pre-sales calls?

Share specific instances where you engaged with customers during pre-sales activities. Explain how you listened to their needs and articulated how your previous role's AI solutions would help address their challenges effectively.

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How do you ensure you are up-to-date with the latest AI trends and technologies?

Reflect on your commitment to lifelong learning through various methods. This could involve attending industry conferences, participating in webinars, contributing to open-source projects, or following AI research publications to stay informed about advancing technologies.

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Can you explain how containerization benefits AI deployments?

Discuss how containerization provides consistency, scalability, and isolation for AI applications. Give examples of how you have utilized it in past roles to simplify the deployment process and maintain efficiency across different environments.

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What strategies do you use when working with large datasets in AI?

Clarify your approach to handling large datasets, such as utilizing efficient data processing frameworks, implementing data pipeline strategies, or leveraging cloud services to manage storage and processing capacity.

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How do you adapt technical communication for different audiences?

Talk about the importance of understanding your audience's background. Provide instances where you adjusted your communication style to convey complex AI concepts clearly for both technical and non-technical stakeholders.

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Describe your experience with infrastructure as code tools.

Share examples of how you have implemented infrastructure as code using tools like Terraform or Ansible. Highlight the benefits of version control, reproducibility, and automation that you realized in your projects.

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Tell us about a time you faced a significant challenge in a project and how you overcame it.

Provide a detailed account of a specific challenge, focusing on your critical thinking and problem-solving skills. Discuss your thought process and the steps taken to navigate the obstacle, leading to a successful resolution.

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What are the key performance indicators you use to measure success in AI implementations?

Discuss your understanding of relevant KPIs such as accuracy, execution time, and user engagement metrics. Explain how you track and analyze these indicators to assess the performance and impact of implemented AI solutions.

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