We are seeking a Senior Consultant, AI/ML Engineer to help operationalize machine learning across a dynamic, mission-driven environment. In this hands-on role, you will build and support the infrastructure, pipelines, and production practices that move models from experimentation to reliable real-world use.
Responsibilities
- Own the end-to-end machine learning lifecycle, including training pipelines, model registry, versioning, promotion, and deployment workflows.
- Design and maintain SageMaker-based training and inference platforms that support production-grade ML services.
- Develop Infrastructure as Code using Terraform for AWS services such as SageMaker, S3, KMS, IAM, CloudWatch, and cross-account access patterns.
- Build and improve CI/CD pipelines to support testing, security scanning, infrastructure validation, and automated model promotion.
- Ensure consistency between training and serving by maintaining shared feature engineering and preprocessing logic.
- Set up monitoring, alerting, and dashboarding for model performance, drift, endpoint health, and operational visibility.
- Support secure and scalable ML operations through least-privilege access, encryption, secrets management, and artifact protection.
- Collaborate closely with data scientists to turn experimental models into tested, reproducible, deployable solutions.
- Support Bedrock-based workflows for batch and real-time use cases, with attention to throughput, cost, and guardrails.
- Help improve incident response and operational efficiency through automation, anomaly detection, and AI-assisted analysis.
Skills
- 5+ years of experience in MLOps, ML platform engineering, or ML infrastructure roles with production ownership of deployed models.
- Strong AWS expertise, especially with SageMaker, S3, IAM, KMS, CloudWatch, Lambda, Step Functions, and multi-account environments.
- Hands-on experience with Terraform and Git-based DevOps workflows.
- Experience designing and maintaining CI/CD pipelines using tools such as GitLab CI, GitHub Actions, or similar platforms.
- Advanced Python development skills for building reliable, production-ready ML tooling and services.
- Solid understanding of model training, evaluation, feature engineering, and metrics such as C-index, AUC, and calibration.
- Experience with model monitoring, drift detection, and production ML support.
- Strong knowledge of security best practices, including least-privilege access, encryption, and secrets management.
- Ability to work cross-functionally and translate technical needs into practical, scalable solutions.
Preferred Skills
- Experience supporting LLM pipelines and Bedrock-based implementations.
- Familiarity with blue/green deployment strategies and automated rollback processes.
- Knowledge of infrastructure and application security tools such as Checkov and SonarQube.
- Exposure to anomaly detection, event-driven automation, and AIOps practices.
- Experience using AI tools to support log analysis, incident triage, or root-cause investigation.
- Background working in highly regulated or operationally sensitive environments.
Horizontal is committed to fostering a workplace where inclusion, equity, and belonging are valued and supported. We welcome candidates from all backgrounds and experiences and are dedicated to building teams that reflect a broad range of perspectives.
By applying for this position, you acknowledge and agree that Horizontal Talent may contact you regarding your application using automated technology, including phone calls, SMS/text messages, or email, which may be delivered by our virtual AI recruiter, Alex.
Please apply through this online posting or by visiting our Job Board at Applications will be accepted for 4 weeks. For those that join the team, we offer competitive compensation and benefits including medical, dental, vision, and retirement. Check out all we have to offer and how you can become part of the Horizontal Talent Team. The pay range for this role is $69 - $107 per hour based on qualifications and experience.
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