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Machine Learning Operations Engineer

2 weeks, 3 days ago
United States
Full-time
Senior
Machine Learning Engineer
DevOps and Infrastructure
CI/CD Docker Grafana Kubernetes Microservices MLflow MLOps NLP Prometheus Python Snowflake System Design
Apply Now
K1x

K1x

K1X is a 'fintech' company specializing in AI automation software for K 1s, K 3s, and 990s. With a team of experts in the financial industry, we aim to revolutionize the K 1 experience by digitizing the traditionally analog process through our cutting-...

Internet Software & Services
51-250
Founded 2022
$15M raised
View All Jobs 8

Description

  • Design and build scalable ML infrastructure to support model training, evaluation, and deployment.
  • Develop and maintain containerized environments using Docker and Kubernetes.
  • Build and manage distributed training pipelines and orchestration workflows.
  • Implement and maintain ML lifecycle tooling such as MLflow for experiment tracking and reproducibility.
  • Own production inference systems, including NVIDIA Triton Inference Server.
  • Design and operate low-latency, high-availability model serving architectures.
  • Implement CI/CD pipelines for ML deployment, versioning, and rollback strategies.
  • Build and maintain data pipelines integrated with Snowflake and related data systems.
  • Implement monitoring, logging, and alerting for model performance, drift detection, and system health.
  • Partner with ML Engineers to improve developer experience and accelerate delivery.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
  • 5+ years of experience in software engineering, DevOps, or MLOps roles.
  • Strong proficiency in Python and experience building production-grade systems.
  • Hands-on experience with Docker, Kubernetes, and distributed systems.
  • Experience building and maintaining CI/CD pipelines.
  • Familiarity with ML lifecycle tools such as MLflow or similar.
  • Experience working with cloud-based data platforms such as Snowflake.
  • Strong understanding of system design, APIs, and microservices architectures.
  • Proven debugging and troubleshooting ability across distributed systems.
  • Experience managing inference infrastructure such as NVIDIA Triton Inference Server (preferred).
  • Experience building large-scale training infrastructure including GPU workloads and distributed training (preferred).
  • Familiarity with feature stores, data versioning, and experiment tracking systems (preferred).
  • Experience supporting NLP or document processing pipelines (preferred).
  • Exposure to observability tools such as Prometheus, Grafana, or similar (preferred).
  • Experience working in SaaS environments with high availability, productivity, and performance requirements (preferred).
  • A strong bias toward automation, scalability, and continuous improvement.
  • A collaborative mindset and ability to work cross-functionally with engineering and data teams.

Benefits

  • Unlimited vacation policy plus sick time and holidays.
  • Fully remote opportunity.
  • Healthcare benefits and 401(k).
  • Paid parental leave.
  • Growing startup culture.

Interested in this position?

Apply directly on the company website

Apply Now

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