[Hiring] Senior Cloud and MLOps Platform Engineer @Mindlance

Role Description

You will be the initial platform engineer on a defense machine learning program in AWS GovCloud building from an internally defined architecture. You will implement the environment as code for a partner operations team to build and run, then build and operate the pipeline that generates physics-based synthetic sensor data, trains and screens models, and records every run as auditable evidence. Later phases move parts of the workload into an air-gapped government high-performance computing center, a separate operating environment with its own rules.

What You Will Do in the First Six Months

• Write Terraform modules, configuration and runbooks that a partner team uses to build and monitor a SageMaker-based environment in GovCloud, and review the result against the definition.
• Wrap a partner's physics simulation engine as containerized SageMaker Processing jobs and orchestrate generation with Step Functions.
• Build training, tuning and inference pipelines on GPU instances within fixed monthly run budgets.
• Build the constraint framework: hard caps, admission control and pre-flight validation, checkpointing and resume, early stopping, and an experiment registry.
• Implement lineage: signed manifests linking every dataset and model to its inputs, code, container digest and configuration.
• Build container images in GitLab CI with offline dependencies, so they also run under Apptainer on a batch-scheduled cluster with no internet access.
• Write clear runbooks and contribute to monthly technical reports.

Qualifications

• Five or more years in cloud or platform engineering, including two or more building machine learning infrastructure on AWS.
• Production Terraform, including modules written for other teams to apply.
• Amazon SageMaker (Processing, Training, hyperparameter tuning, endpoints) and Step Functions.
• Docker and CI/CD (GitLab preferred), with images pinned by digest and dependencies vendored.
• AWS security fundamentals: IAM least privilege, KMS customer managed keys, VPC endpoints and PrivateLink, Secrets Manager.
• Experience in a regulated environment: AWS GovCloud, FedRAMP High, DoD IL4/IL5, or CUI under NIST SP 800-171.
• Strong Python.

Preferred

• HPC experience: Slurm or PBS, Apptainer or Singularity, Lustre, offline software stacks.
• MLflow or a comparable experiment tracker; SageMaker Model Monitor.
• AWS cost controls and FinOps for GPU workloads.
• Multi-account AWS Organizations under Control Tower, Lake Formation, API Gateway.
• DoD Risk Management Framework documentation or CMMC.
• AWS certifications (Solutions Architect Professional, Machine Learning, Security).

Working Arrangement

This is a remote role, open to candidates anywhere in the United States. Company provides the hardware and a company-managed laptop.

Citizenship and Clearance

U.S. citizenship required. An active Secret clearance is a bonus; eligibility to obtain one required.

EEO

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”