Machine Learning & Data Engineer

TL;DR

Principal Machine Learning & Data Engineer (AI/AWS): Leading the design, build, and operation of an internal ML-and-data platform that powers customer interactions with an accent on cloud-native pipelines, model-serving infrastructure, and MLOps best practices. Focus on architecting reliable, secure, and cost-efficient systems, implementing automated testing and CI/CD for high-volume workloads, and ensuring compliance with stringent privacy requirements.

Location: Remote (US), not eligible to be hired in CA, CT, NJ, NY, PA, WA

Salary: $184,500 - $271,300

Company

hirify.global is a product company shaping the future of communications, delivering innovative solutions and empowering developers worldwide to craft personalized customer experiences.

What you will do

• Architect and evolve hirify.global’s end-to-end ML and real-time data platforms for reliability, security, and cost efficiency.
• Design scalable feature stores, streaming and batch pipelines, and low-latency model-serving layers on AWS.
• Implement MLOps best practices—automated testing, CI/CD, monitoring, and rollback—for hundreds of daily deployments.
• Own system design reviews, threat modeling, and performance tuning for high-volume communications workloads.
• Lead cross-functional engineering efforts, breaking down complex initiatives into executable roadmaps.
• Mentor staff and senior engineers, raising the technical bar through code reviews and pair programming.

Requirements

• Bachelor’s or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• 7+ years building and operating production data or machine-learning systems at scale.
• Expert fluency in Python and one compiled language (Java, Scala, Go, or C++).
• Hands-on mastery of distributed data frameworks (Spark/Flink), SQL/NoSQL stores, and streaming platforms (Kafka/Kinesis).
• Demonstrated success designing cloud-native architectures on AWS, including Terraform-managed infrastructure.
• Deep knowledge of container orchestration (Kubernetes/EKS), service-mesh networking, and autoscaling strategies.
• Practical experience implementing MLOps tooling such as MLflow, Kubeflow, SageMaker, or Vertex AI.

Nice to have

• Graduate degree focused on machine learning, distributed systems, or applied statistics.
• Contributions to open-source ML or data infrastructure projects.
• Experience with privacy-enhancing technologies (differential privacy, homomorphic encryption) or on-device inference.
• Background in conversational AI, real-time communications, or large-language-model deployment at scale.

Culture & Benefits

• Remote-first work culture with a strong emphasis on connection and global inclusion.
• AI used to make the hiring process efficient, fair, and transparent, with all final decisions made by humans.
• Competitive pay, generous time off, and ample parental and wellness leave.
• Comprehensive healthcare and a retirement savings program.
• Empowerment to build positive change in communities through volunteering and donation efforts.

Hiring process

• Applications for this role are intended to be accepted until May 21st 2026.