2 дня назад
Sr. ML Engineer (AI)
123 400 - 191 100$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Sr. ML Engineer (AWS/Kubernetes/MLOps): Building and operating scalable ML platform infrastructure, pipelines, orchestration frameworks, and model-serving environments for AI/ML applications with an accent on secure cloud and on-premise infrastructure, GPU workloads, and productionization. Focus on modernizing legacy ML pipelines, enabling Data Scientists and AI Engineers to deploy models, and designing reliable platforms for GenAI and LLM workloads.
Location: US - Austin, TX; at least 3 days per week in the office. Travel required 5–10% of the time.
Salary: $123,400–$191,100 USD per year, with potential bonus and equity eligibility.
Company
operates a global payments technology network connecting consumers, merchants, financial institutions, and government entities.
What you will do
- Build and maintain scalable ML platform infrastructure, pipelines, orchestration frameworks, and model-serving environments.
- Develop tooling that helps Data Scientists and AI Engineers move models from research into production.
- Operate secure cloud and on-premise infrastructure using AWS, Kubernetes, SageMaker, Terraform, and related technologies.
- Support GPU-enabled infrastructure and serving frameworks for AI/ML, generative AI, and LLM workloads.
- Modernize legacy ML pipelines and improve platform reliability, scalability, and operational efficiency.
- Define platform architecture, implementation standards, and best practices while collaborating with engineering, infrastructure, security, and data teams.
Requirements
- At least 3 days per week in the Austin office is required.
- At least 2 years of relevant experience with a bachelor's degree, or 5+ years of relevant experience.
- Experience designing and operating scalable ML platform infrastructure for AI/ML applications.
- Experience with AWS services, Kubernetes, Docker, ML pipelines, orchestration tools, and Infrastructure as Code.
- Experience with Python or shell scripting, CI/CD, secure cloud architecture, and production model deployment.
- Experience with GPU orchestration, ML serving frameworks, hybrid or on-premise infrastructure, and distributed ML workloads.
Nice to have
- Experience with generative AI, large language models, LLMOps, or GenAI infrastructure.
- Experience with vLLM, TensorRT-LLM, KServe, Triton, Spark, Kubeflow, Airflow, or MLflow.
- Experience using AI-assisted engineering tools such as GitHub Copilot or ChatGPT.
- Experience mentoring junior engineers and leading key platform modules.
Culture & Benefits
- Work in an enterprise and regulated environment on payment technology used across more than 200 countries and territories.
- Medical, dental, and vision coverage.
- 401(k), FSA/HSA, life insurance, paid time off, and wellness program.
- Work hours vary according to department needs.
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