5 часов назад
Software Engineer AI/ML Ops
145 000 - 182 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Software Engineer AI/ML Ops (AI/ML, PySpark): Building and optimizing data pipelines and infrastructure for AI-driven accounting agents with an accent on production ML operations, data integrations, and pipeline reliability. Focus on scaling ML and LLM systems, automating testing and deployment, and monitoring model and agent performance across cloud environments.
Location: Pleasanton, United States; candidates within a reasonable commute to an office must work onsite at least 3 days per week
Salary: $145,000–$182,000 per year
Company
develops finance automation technology, including AI-driven accounting agents.
What you will do
- Build and maintain high-quality, high-performance PySpark ETL and data pipelines.
- Integrate client data sources through APIs, FiveTran, Plaid, and internal connector systems.
- Monitor pipeline performance, automate testing, and validate data accuracy.
- Improve scalability through CDC mechanisms, indexing strategies, and other performance optimizations.
- Operate production pipelines for ML and LLM-based systems across GCP, AWS, and Azure.
- Collaborate with business stakeholders to refine data requirements and integrate AI and big data technologies.
Requirements
- 2+ years of programming experience with Python, Java, or Scala.
- Expertise with ML frameworks such as TensorFlow, PyTorch, or scikit-learn, and orchestration tools such as Airflow, Kubeflow, Vertex AI, or MLflow.
- Experience with LangChain, LangGraph, ADK, or similar agentic system runtimes.
- Strong CI/CD, infrastructure-as-code, and DevSecOps skills, including testing, compliance, and deployment automation.
- Experience with Prometheus, Grafana, New Relic, or similar observability tools for tracking model and agent performance.
- Understanding of Responsible AI governance, auditability, cost metering, Docker, and Kubernetes.
Nice to have
- Bash or Python scripting for automation.
- Experience managing and optimizing cloud infrastructure and Apache Airflow workflows.
- Knowledge of network configurations and security protocols.
- Strong problem-solving skills and the ability to evaluate models, identify limitations, and adapt to evolving AI and data science technologies.
Culture & Benefits
- Professional development seminars and learning opportunities.
- Inclusive affinity groups and a diverse, accepting workplace culture.
- Short-term and long-term incentive programs, subject to eligibility.
- Benefit and wellness plans.
- Virtual and in-person collaboration designed to support teamwork and company culture.
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