At a Glance
- Tasks: Build innovative AI/ML solutions and collaborate with top engineers and data scientists.
- Company: Join a forward-thinking tech firm focused on AI and machine learning.
- Benefits: Competitive salary, flexible work options, and opportunities for skill development.
- Other info: Dynamic team environment with a focus on continuous improvement and growth.
- Why this job: Shape the future of technology and make a real impact on global projects.
- Qualifications: Experience in AWS, resilient software platforms, and strategic solution design.
The predicted salary is between 80000 - 100000 £ per year.
Are you passionate about building innovative technology that powers AI and machine learning across a global organization? As part of our team, you’ll help shape the future of model deployment at scale, collaborating with talented engineers and data scientists. You’ll have the opportunity to work on impactful projects, grow your skills, and contribute to a platform that drives real business outcomes. We value creativity, collaboration, and a commitment to excellence.
As a Software Engineer in the Firmwide AI/ML Deployment Platform team, you will design and develop cloud-native solutions that support model deployment across the organization. You will work closely with data scientists and engineers to deliver features that streamline production workflows. Your contributions will help scale our platform to meet the needs of diverse internal clients, ensuring reliability and innovation. You will be part of a collaborative environment focused on continuous improvement and technical excellence.
Job Responsibilities- Build and deploy infrastructure solutions for seamless integration of control plane and client accounts
- Develop and implement APIs for platform functionalities such as automated retraining, scheduling, endpoint deployments, and autoscaling
- Design robust features to support a growing internal customer base, including multi-region and disaster recovery capabilities
- Architect and implement model monitoring solutions, with emphasis on LLM monitoring and automated issue correction
- Engage with clients to identify strategic solutions and provide deployment and debugging support
- Assist in implementing platform capabilities aligned with product requirements
- Deploy infrastructure and develop managed environments for platform operations
- Knowledge of AWS services and cloud-based infrastructure
- Experience building resilient software platforms
- Proficiency in architecting software solutions at scale
- Ability to design solutions with strategic insight
- Familiarity with monitoring tools, especially for AI/ML model monitoring
- Proficiency in Golang
- Experience with AWS Sagemaker for model training and deployment
- Familiarity with Kubernetes and managing deployments to EKS
- Knowledge of networking concepts such as Virtual Private Clouds and DNS
- Experience working with LLMs
- Experience with Terraform or other Infrastructure as Code tools
- Experience in API development and design
Lead Software Engineer - AWS - Lead AI/ML Platform Engineer in London employer: Jpmorgan Chase & Co.
Join a forward-thinking organisation that champions innovation and collaboration in the realm of AI and machine learning. As a Lead Software Engineer, you will thrive in a dynamic work culture that prioritises creativity and continuous improvement, while enjoying ample opportunities for professional growth and skill enhancement. Located in a vibrant tech hub, our company offers a unique environment where your contributions directly impact real business outcomes, making it an exceptional place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - AWS - Lead AI/ML Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those who work with AI and ML. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS and AI/ML. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to cloud-native solutions and APIs. Practising coding challenges can also help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our innovative team.
We think you need these skills to ace Lead Software Engineer - AWS - Lead AI/ML Platform Engineer in London
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for AI and machine learning shine through. We want to see how excited you are about building innovative technology and shaping the future of model deployment!
Tailor Your Experience:Make sure to highlight your relevant experience with AWS services and cloud-native solutions. We’re looking for specific examples that demonstrate your skills in building resilient software platforms and architecting solutions at scale.
Be Collaborative:Since we value collaboration, mention any experiences where you’ve worked closely with engineers or data scientists. Show us how you’ve contributed to team projects and helped deliver impactful results.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get you into our system quickly. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of AWS services and cloud-based infrastructure. Be ready to discuss how you've built resilient software platforms in the past, and have specific examples at hand that showcase your experience with APIs, Terraform, and Kubernetes.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in deploying AI/ML models. Think of scenarios where you identified strategic solutions or provided debugging support. This will demonstrate your ability to engage with clients and deliver impactful results.
✨Emphasise Collaboration
Since this role involves working closely with data scientists and engineers, be ready to share experiences where collaboration led to successful outcomes. Highlight any projects where teamwork was key to designing robust features or improving production workflows.
✨Stay Current with Trends
Familiarise yourself with the latest trends in AI/ML and cloud technologies. Being able to discuss recent advancements or tools, especially around LLM monitoring and automated issue correction, will show your passion for continuous improvement and technical excellence.
