Senior MLOps & AI Infrastructure Engineer at Altera - ScoutJobs - The AI-curated global job board
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Posted 21 days ago

Senior MLOps & AI Infrastructure Engineer

AlteraSenior MLOps & AI Infrastructure Engineer

Requirements

Bachelor's or Master's in CS, ML, or Statistics, 10+ years industry experience, 10+ years ML engineering and MLOps experience, 8+ years parallelism strategies (FSDP, DeepSpeed), 10+ years Python proficiency, 8+ years cloud ML platforms and Kubernetes, 5+ years MLflow, W&B, or Neptune

Skills

MLOpsPythonKubernetesPyTorchAWSTerraformDocker

About the role

Responsibilities

  • Architect, build, and maintain scalable ML pipelines for training, evaluation, and deployment across cloud and on-prem HPC environments
  • Build MLOps infrastructure including experiment tracking, model registry, feature stores, and automated retraining workflows
  • Implement CI/CD/CT pipelines for ML models using tools such as Kubeflow, MLflow, or Airflow
  • Containerize ML workloads with Docker and orchestrate at scale using Kubernetes and GPU node pools
  • Develop, fine-tune, and deploy large-scale models including LLMs, GNNs, and reinforcement learning agents
  • Manage cloud ML infrastructure on AWS, Azure, or GCP with cost and performance optimization
  • Automate infrastructure provisioning using Terraform or CloudFormation for GPU-backed environments
  • Build monitoring, alerting, and observability systems for model performance drift and system health

Requirements

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related field
  • 10+ years of industry experience, including 10+ years in ML engineering and MLOps
  • 8+ years of experience with parallelism strategies such as FSDP, DeepSpeed, or data/model parallelism
  • 10+ years of proficiency in Python programming
  • 8+ years of experience with cloud ML platforms (AWS, GCP, Azure), Docker, Kubernetes, and CI/CD pipelines
  • 5+ years of hands-on experience with MLflow, W&B, or Neptune for tracking and reproducibility

Preferred Qualifications

  • PhD in Computer Science, Machine Learning, or Statistics
  • Experience applying ML/AI to semiconductor, EDA, or chip design domains
  • Familiarity with HPC schedulers such as LSF or Slurm and GPU cluster management
  • Knowledge of LLM fine-tuning, RAG architectures, and AI agent frameworks like LangChain
  • Experience with graph neural networks (GNNs) or geometric deep learning
  • Background in reinforcement learning for optimization problems

About the Company

Altera is the world’s largest pure-play FPGA solutions provider, delivering programmable technologies that help customers innovate across AI, cloud, networking, and edge markets. As an independent company, Altera focuses on providing leadership programmable solutions that are easy to use and deploy, helping to shape the future of the semiconductor industry.

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Senior MLOps & AI Infrastructure Engineer

Altera · San Jose

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