This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Artificial Intelligence & Machine Learning Architect SME in the United States.
This role provides a unique opportunity to lead AI and machine learning architecture initiatives for large-scale, cloud-based enterprise solutions. You will define, implement, and maintain AI/ML pipelines, ensuring scalability, performance, and compliance with federal standards. The position involves working with cross-functional teams to integrate AI/ML solutions into enterprise applications, optimize model performance, and apply MLOps best practices. Ideal candidates will be experienced in cloud-based ML infrastructure, Python programming, containerization, and have a strong understanding of responsible AI practices. This is a chance to influence critical modernization programs while working in a dynamic, innovative environment.
Accountabilities
- Define, document, and maintain scalable, modular AI/ML architecture aligned with enterprise cloud strategy.
- Architect and implement end-to-end AI/ML pipelines including data ingestion, feature engineering, model training, deployment, monitoring, and retraining.
- Apply MLOps best practices for continuous integration, delivery, and lifecycle management of machine learning models.
- Ensure AI/ML workloads are elastic, highly available, and cost-efficient across multi-tenant, multi-region environments.
- Utilize Infrastructure-as-Code (IaC) tools to provision and manage cloud-based AI/ML infrastructure in compliance with federal security standards.
- Design secure, reusable, and performant AI/ML services and APIs for enterprise consumption.
- Conduct model validation, optimization, and maintain documentation with transparency and responsible AI principles.
- Advise teams on third-party ML tools, frameworks, and SaaS integrations in a secure and compliant manner.
Requirements
- 15+ years of experience in AI/ML architecture, cloud development, or related information systems.
- Proven success architecting and deploying ML workflows in cloud environments (AWS SageMaker, Azure ML, GCP Vertex AI).
- Hands-on experience with ML/DL frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost, or Keras.
- Strong programming skills in Python, with experience in containerization (Docker) and orchestration (Kubernetes).
- Experience with MLOps tools (MLflow, Kubeflow, TFX, Airflow) and CI/CD integration for model deployment.
- Familiarity with federal data governance, security, and privacy standards, including JISF, NIST 800-53, and FedRAMP.
- Proficiency with IaC tools such as Terraform, CDK, or CloudFormation.
- Knowledge of multi-tenant, distributed systems, and cloud-native architecture patterns.
- Relevant certifications (AWS Certified Machine Learning – Specialty, Google Professional ML Engineer) preferred.
- Must be a US Person (Green Card, Permanent Resident, Asylee, US Citizen) and able to obtain a position of Public Trust.
Benefits
- Competitive salary commensurate with experience ($191,404 - $258,958 range).
- Hybrid or remote work options.
- 401(k) with company match and comprehensive health, dental, and vision coverage.
- Paid vacation, holidays, parental leave, and additional flexible leave programs.
- Professional growth opportunities, including paid education, certifications, and internal mobility support.
- Exposure to large-scale, mission-critical AI/ML modernization projects in a collaborative environment.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.