Sr. ML Engineer

Salary: $123,400 - 191,100 per year Requirements:

• We require 2+ years of relevant experience with a bachelors degree, or 5+ years of relevant experience.
• We prefer 4 or more years of relevant hands-on experience in a specialist capacity.
• We look for experience designing, building, and supporting scalable ML platform infrastructure for AI/ML workloads.
• We value experience with AWS services such as EC2, S3, EKS, SageMaker, IAM, VPC, and CloudWatch.
• We seek experience managing Kubernetes clusters and containerized ML workloads with Docker.
• We look for familiarity with ML pipeline and orchestration tools such as Kubeflow, Airflow, MLflow, or similar platforms.
• We prefer experience automating infrastructure with Terraform, CloudFormation, or other infrastructure-as-code tools.
• We value experience developing CI/CD pipelines for ML deployment and infrastructure updates.
• We seek experience implementing secure cloud architectures using IAM roles, VPCs, least-privilege access, and secure networking patterns.
• We look for Python and shell scripting experience for automation, tooling, and platform operations.
• We prefer experience partnering with Data Scientists, AI Engineers, and cross-functional teams to move models from research to production.
• We value exposure to generative AI, large language models, LLMOps, or GenAI infrastructure.
• We seek experience with GPU orchestration for training, inference, capacity planning, and workload optimization.
• We prefer experience with ML serving frameworks such as vLLM, TensorRT-LLM, KServe, Triton, or similar technologies.
• We look for experience building and operating hybrid cloud or on-prem and cloud ML infrastructure.
• We value experience with distributed computing frameworks such as Spark or other distributed ML workloads.
• We prefer experience using AI-assisted productivity tools such as GitHub Copilot, ChatGPT, or similar tools.
• We look for experience building robust, secure, and scalable platforms in enterprise or regulated environments.
• We value research, experimentation, or proof-of-concept work with emerging AI/ML infrastructure technologies.
• We prefer experience mentoring junior engineers and leading the implementation of key platform modules.

• We lead and deliver specific platform engineering initiatives as a Senior ML Engineer.
• We guide the engineering team on scalable ML infrastructure, deployment patterns, and platform capabilities.
• We build tooling that improves productivity for Data Scientists and AI Engineers by simplifying model deployment and productionization.
• We act as a platform design authority and help shape best practices and methods within the ML platform team.
• We design and build scalable ML pipelines, orchestration frameworks, and model serving infrastructure.
• We collaborate with Data Scientists, AI Engineers, infrastructure teams, and security partners to bring AI/ML solutions into production.
• We build and operate secure cloud and on-prem infrastructure using AWS, Kubernetes, SageMaker, Terraform, and related technologies.
• We support GPU-enabled infrastructure and serving frameworks for AI/ML, GenAI, and LLM workloads.
• We modernize legacy ML pipelines and adopt emerging technologies to improve reliability, scalability, and operational efficiency.
• We communicate technical concepts, platform capabilities, and architectural decisions to both technical and non-technical stakeholders.
• We work in an office setting with at least 3 days per week in office, with the schedule confirmed by the Hiring Manager.
• We travel approximately 5-10% of the time.

• AI
• Airflow
• AWS
• ChatGPT
• CI/CD
• Cloud
• CloudWatch
• Copilot
• Docker
• EC2
• GitHub
• IAM
• Support
• Kubeflow
• Kubernetes
• LLM
• MLflow
• Model Serving
• Python
• Security
• Spark
• Terraform
• vLLM
• MLOps

More:

We are Visa, a global leader in payments technology, facilitating transactions between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories. We are committed to uplifting everyone, everywhere by being the best way to pay and be paid. In this role, you will help build the ML platform infrastructure that powers AI and ML applications across our organization, contributing to scalable tooling, production-ready deployment environments, and modernization efforts that help Data Scientists and AI Engineers move models from research to production. We offer a comprehensive benefits package that may include Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and a Wellness Program, and this position may also be eligible for bonus and equity. The estimated US salary range for this role is $123,400 to $191,100 USD per year, depending on job-related factors such as knowledge, skills, experience, and location.

last updated 41 week of 2026