Senior Consultant, AI/ML Engineer
Listed on 2026-08-22
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IT/Tech
Machine Learning/ ML Engineer, AWS, AI Engineer (Applied/Software), SRE/Site Reliability
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 Sage Maker-based training and inference platforms that support production-grade ML services.
- Develop Infrastructure as Code using Terraform for AWS services such as Sage Maker, S3, KMS, IAM, Cloud Watch, 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.
- 5+ years of experience in MLOps, ML platform engineering, or ML infrastructure roles with production ownership of deployed models.
- Strong AWS expertise, especially with Sage Maker, S3, IAM, KMS, Cloud Watch, Lambda, Step Functions, and multi‑account environments.
- Hands‑on experience with Terraform and Git‑based Dev Ops workflows.
- Experience designing and maintaining CI/CD pipelines using tools such as Git Lab CI, Git Hub 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.
- 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 Sonar Qube.
- 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.
For those that join the team, we offer competitive compensation and benefits including medical, dental, vision, and retirement. The pay range for this role is $69 - $107 per hour based on qualifications and experience. Applications will be accepted for 4 weeks.
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