At a Glance
- Tasks: Build high-performance AI platforms and deploy cutting-edge NLP models.
- Company: Join a leading tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative team environment with exciting challenges and career advancement.
- Why this job: Make a real impact in the AI space while working with advanced technologies.
- Qualifications: 5+ years in engineering, experience with Kubernetes, and strong coding skills.
The predicted salary is between 70000 - 90000 € per year.
Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications?
- 5+ years of engineering experience running production infrastructure at a large scale
- Experience designing large, highly available distributed systems with Kubernetes and GPU workloads on those clusters
- Experience with Kubernetes dev and production coding and support
- Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving
- Experience in designing, deploying, supporting, and troubleshooting in complex Linux-based computing environments
- Experience in compute/storage/network resource and cost management
- Excellent collaboration and troubleshooting skills to build mission-critical systems, and ensure smooth operations and efficient teamwork
- The grit and adaptability to solve complex technical challenges that evolve day to day
- Familiarity with computational characteristics of accelerators (GPUs, TPUs, and/or custom accelerators), especially how they influence latency and throughput of inference
- Strong understanding or working experience with distributed systems
- Experience in Golang, C++ or other languages designed for high-performance scalable servers
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!
What the job involves:
We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs.
Staff Software Engineer (Inference Infrastructure) employer: Deepstreamtech
Cohere is an exceptional employer for Staff Software Engineers, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of AI. With a strong emphasis on employee growth, you will have access to cutting-edge technology and the opportunity to work alongside industry experts, all while enjoying the benefits of a supportive environment that values your contributions. Located in a vibrant tech hub, Cohere provides unique advantages such as networking opportunities and a diverse community of like-minded professionals.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer (Inference Infrastructure)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to machine learning and distributed systems. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and system design knowledge. Practice common algorithms and data structures, and be ready to discuss your experience with Kubernetes and cloud platforms.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff Software Engineer (Inference Infrastructure)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with high-performance systems and distributed architectures. We want to see how your skills align with our needs, so don’t be shy about showcasing your Kubernetes and cloud experience!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re excited about building AI platforms and how your background makes you a perfect fit for the role. Keep it engaging and personal – we love to see your passion!
Showcase Your Problem-Solving Skills:In your application, share examples of complex challenges you've tackled in previous roles. We’re looking for grit and adaptability, so let us know how you’ve navigated tricky situations in production environments.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kubernetes, GCP, and distributed systems. Brush up on your knowledge of how these systems work together, as you might be asked to explain your experience with them during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly those involving high-performance systems or complex Linux environments. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your adaptability and troubleshooting skills.
✨Collaborate and Communicate
Since this role involves working closely with various teams, be ready to demonstrate your collaboration skills. Share examples of how you’ve successfully worked in a team setting, and don’t forget to mention any experience interfacing with customers to tailor solutions to their needs.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI platform and the Model Serving team’s goals. This shows your genuine interest in the role and helps you understand how you can contribute to their mission of delivering advanced NLP applications.
