As a Software Engineer, in this role you will be able to achieve state-of-the-art throughput for critical models using advanced techniques such as model parallelism and distributed training. You will be working to reduce inference time for new model architectures using optimizations such as quantization and pruning. You will collaborate closely with Applied AI engineering to optimize the internal inference stack. Collaborate with top-tier AI systems engineers, fostering a culture of continuous learning and innovation, while coordinating the inference needs of JPMC's research teams, ensuring alignment with business goals.

As a Software Engineer III at JPMorgan Chase within the Corporate Sector AI/ML Technologies Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a Software Engineer in this role, you will get to drive significant business impact using your technical capabilities and contributions and apply deep technical prowess and problem-solving skills to tackle a diverse array of challenges that span multiple technologies and applications in the AI/ML space.

Job responsibilities

Implements distributed ML infrastructure, including inference, training, scheduling, orchestration, and storage. Develops advanced monitoring and management tools for high reliability and scalability. Optimizes system performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product teams to deliver tailored, technology-driven solutions. Helps with the adoption and execution of ML Platform tools across various teams. Integrates Generative AI within the ML Platform using state-of-the-art techniques.  Develops secure and high-quality production code, and reviews and debugs code written by others. Drives decisions that influence the product design, application functionality, and technical operations and processes. Serves as a function-wide subject matter expert in one or more areas of focus. Actively contributes to the engineering community as an advocate of firm wide frameworks, tools, and practices SDLC. Analyzes, writes, develops, tests, and releases the products using Python on AWS

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 3+ years applied experience. Hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, RAY).  Experience in AWS / GCP and Kubernetes ecosystem, including EKS, Helm, and custom operators. Strong coding skills and experience in developing large-scale ML systems.  Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems. Proven track record in contributing to and optimizing open-source ML frameworks. Advanced in one or more programming language(s) – Python or Java, Intermediate Python is a must.  Proven ability to identify trade-offs, clarify project ambiguities, and drive decision-making.

Preferred qualifications, capabilities, and skills 

Undergraduate degree in Computer Science or Data Science Experience in building Generative AI based system Experience in continuous integration and continuous deployment platform