Fortive

Senior Platform Engineer

Fortive

full-time

Posted on:

Location Type: Remote

Location: India

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Job Level

Senior

Tech Stack

AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformGrafanaKafkaKubernetesPrometheusPythonPyTorchSparkTensorflowTerraform

About the role

  • Design and maintain AI/ML platform infrastructure, including compute clusters (CPU/GPU), storage systems, and networking for high-performance workloads.
  • Develop internal tools and automation to streamline workflows across data preparation, model training, evaluation, and deployment.
  • Implement Infrastructure as Code (IaC) for reproducible environments and automated provisioning (Terraform, CloudFormation).
  • Build and manage Kubernetes clusters and container orchestration for ML services and pipelines.
  • Integrate observability and monitoring for platform health, resource utilization, and ML workloads.
  • Optimize cost and performance for compute-intensive ML tasks, including GPU scheduling and autoscaling.
  • Collaborate with MLOps Engineers to enable CI/CD pipelines for ML models and data workflows.
  • Ensure platform security and compliance, including IAM, secrets management, and network policies.
  • Support feature stores, model registries, and experiment tracking systems to accelerate ML development.
  • Drive innovation by introducing new tools and frameworks that improve productivity and reduce time-to-market for AI solutions.

Requirements

  • 5+ years of experience in platform engineering, DevOps, or infrastructure roles.
  • Strong proficiency with cloud platforms (AWS, GCP, Azure) and managed ML services.
  • Expertise in containerization and orchestration (Docker, Kubernetes).
  • Experience with Infrastructure as Code (Terraform, CloudFormation).
  • Familiarity with CI/CD pipelines and automation frameworks.
  • Solid understanding of networking, security, and distributed systems.
  • Proficiency in scripting and automation (Python, Bash).
  • Experience supporting AI/ML workloads (GPU clusters, ML frameworks like TensorFlow or PyTorch).
  • Knowledge of data engineering fundamentals and big data technologies (Spark, Kafka).
  • Familiarity with MLOps tooling (MLflow, Kubeflow, TFX).
  • Hands-on experience with observability tools (Prometheus, Grafana).
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
  • Certifications in cloud architecture or Kubernetes (CKA/CKAD) are a plus.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
AI/ML platform infrastructureInfrastructure as CodeTerraformCloudFormationKubernetesDockerPythonBashTensorFlowPyTorch
Soft skills
collaborationinnovationproblem-solvingcommunication
Certifications
CKACKAD