Senior Lead Software Engineer- AI Platform engineer
- Provide technical guidance and direction to support business objectives, collaborating with technical teams, contractors, and vendors.
- Develop secure, high-quality production code, and review and debug code written by others.
- Influence product design, application functionality, and technical operations through informed decision-making.
- Advocate for firmwide frameworks, tools, and practices within the Software Development Life Cycle.
- Promote a culture of diversity, equity, inclusion, and respect within the team.
- Architect and deploy secure, scalable cloud infrastructure platforms optimized for AI and machine learning workloads.
- Collaborate with AI teams to translate computational needs into infrastructure requirements.
- Monitor, manage, and optimize cloud resources for performance and cost efficiency.
- Design and implement continuous integration and delivery pipelines for machine learning workloads.
- Develop automation scripts and infrastructure as code to streamline deployment and management tasks.
Required Qualifications:
- Formal training or certification in software engineering concepts with 5+ years of applied experience.
- Hands-on experience in system design, application development, testing, and operational stability.
- Proficiency in at least one programming language, such as Python, Go, Java, or C#.
- Ability to independently tackle design and functionality problems with minimal oversight.
- Background in Computer Science, Computer Engineering, Mathematics, or a related technical field.
- Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud).
- Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
- Experience in solutions design and engineering, containerization (Docker, Kubernetes), and cloud service providers (AWS, Azure, GCP).
- Experience with Infrastructure as Code.
- Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, and routing/switching technologies.
- Foundational understanding of NVIDIA GPU infrastructure software (e.g., DCGM, BCM, Triton Inference).
- Hands-on experience with machine learning frameworks such as PyTorch and TensorBoard.
- Proficiency with observability tools like Prometheus and Grafana.
- Experience in ML Ops and related tooling, including MLflow.
- Background in high performance computing and ML frameworks (e.g., vLLM, Ray.io, Slurm).
- Strong knowledge of network architecture, database programming (SQL/NoSQL), and data modeling.
- Familiarity with cloud data services, big data processing tools, and Linux environments (scripting and administration).
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans Base Pay/Salary
Jersey City,NJ $171,000.00 - $260,000.00 / year
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