Senior AI/ML Platform Engineer (AI/ML)

Location: McLean, Virginia, United States; hybrid with 3 days per week onsite. US citizenship is required, and candidates must be eligible to obtain and maintain access to AWS GovCloud secure environments. Candidates based in the Tysons vicinity will be prioritized.

Annual base salary: $148,500–$221,000.

Company

hirify.global provides hirify.global Experience Cloud, a SaaS platform for managing experiences, insights, and actions for customers, employees, patients, residents, and candidates.

What you will do

• Lead the migration of AI/ML platform services to AWS GovCloud while meeting compliance, security, and performance standards.
• Design and implement cloud-native ML infrastructure using AWS services, including SageMaker, ECS, EKS, and Lambda.
• Monitor, maintain, and optimize deployed models and ML pipelines in GovCloud environments.
• Build secure data pipelines across national boundaries in accordance with FedRAMP requirements.
• Architect scalable large-scale data processing solutions and design APIs for front-end applications.
• Automate manual processes, improve data delivery and infrastructure scalability, collaborate with product and design teams, and participate in scheduled on-call rotations.

Requirements

• US citizenship and eligibility to obtain and maintain access to AWS GovCloud secure environments.
• BA/BS degree in Computer Science or a related technical discipline, or equivalent practical experience.
• 5+ years of production software development experience using Python, Java, or Scala.
• Experience deploying and operating services on Kubernetes, including familiarity with Kubernetes-based deployment frameworks in regulated environments.
• Experience with distributed systems including Spark, Hadoop, and Kafka.
• Experience with relational SQL databases, including Postgres.
• Experience applying code quality best practices and testing architectures across large codebases.

Nice to have

• Familiarity with AWS services including EC2, S3, IAM, VPC, EKS, and SageMaker for native AWS deployments outside the company’s Kubernetes framework.
• Experience with AWS GovCloud or FedRAMP-compliant environments.
• AWS Certified Machine Learning Specialty or Solutions Architect certification.
• Experience with ML model serving platforms such as TensorFlow Serving, TensorRT, Triton, or KServe.
• Experience with data pipeline and workflow management tools such as Airflow or Kubeflow.
• Microservices development using Django or Spring.
• Experience with NoSQL databases, including Elasticsearch.

Culture & Benefits

• Medical, dental, and vision benefits.
• 401(k), disability, life and AD&D insurance.
• Statutory leaves, paid parental leave, and paid holidays.
• Equal opportunity workplace committed to diversity and pay transparency.