At a Glance
- Tasks: Build innovative AI/ML solutions and collaborate with top engineers and data scientists.
- Company: Join a leading tech firm focused on cutting-edge AI technology.
- Benefits: Competitive salary, flexible work options, and opportunities for skill development.
- Other info: Dynamic team culture with a focus on continuous improvement and career growth.
- Why this job: Shape the future of AI deployment and make a real impact in a collaborative environment.
- Qualifications: Experience with AWS and resilient software platforms; strong problem-solving skills.
The predicted salary is between 70000 - 90000 £ 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 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
✨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 related to 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 technical interviews by brushing up on your coding skills and understanding cloud-native solutions. Practice common algorithms and system design questions to boost your confidence.
✨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
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-based infrastructure. We’re looking for specific examples that demonstrate your ability to design and develop robust software solutions at scale.
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured responses that get straight to the heart of your skills and experiences, especially when it comes to API development and deployment.
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 ensures you’re considered for this exciting opportunity in our Firmwide AI/ML Deployment Platform team.
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS services and cloud-based infrastructure. Brush up on your knowledge of APIs, Terraform, and Kubernetes, as these are crucial for the role. Being able to discuss specific projects where you've implemented these technologies will show your expertise.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, especially around model deployment and monitoring. Think of examples where you’ve designed resilient software platforms or improved workflows. This will demonstrate your strategic insight and ability to deliver impactful solutions.
✨Engage with Real Scenarios
Be ready to engage in discussions about real-world scenarios related to AI/ML deployment. You might be asked how you would approach a specific problem or project. Practising these scenarios can help you articulate your thought process and collaborative approach effectively.
✨Emphasise Collaboration and Creativity
Since the role involves working closely with data scientists and engineers, highlight your experience in collaborative environments. Share examples of how you’ve contributed to team success and fostered creativity in your projects. This aligns perfectly with the company’s values and will set you apart.
