- Company Name
- Apex Systems
- Job Title
- AI/ML Architect
- Job Description
-
**Job Title:** AI/ML Architect
**Role Summary:**
Lead the design and deployment of scalable, secure AI/ML solutions across the enterprise. Translate business use cases into technical architectures, set reference models for GenAI, ML, NLP, and predictive analytics, and embed responsible AI practices into production workflows.
**Expectations:**
- Deliver end‑to‑end AI/ML architectures that meet performance, scalability, and security requirements.
- Establish and enforce governance, fairness, and explainability standards for AI models.
- Mentor data science and engineering teams, promoting best practices in MLOps and AI engineering.
**Key Responsibilities:**
- Design data ingestion, feature engineering, model development, deployment, and monitoring pipelines.
- Define enterprise AI reference architectures for GenAI, ML, NLP, and predictive analytics.
- Select, standardize, and champion AI platforms, frameworks, and tools.
- Collaborate with business, data, and engineering leaders to translate use cases into technical solutions.
- Work with data architecture teams to ensure data quality, lineage, and governance for AI workloads.
- Implement Responsible AI principles (fairness, explainability, bias mitigation).
- Design and implement MLOps/LLMOps CI/CD, versioning, monitoring, and retraining frameworks.
- Provide architectural leadership and mentorship to data scientists and ML engineers.
**Required Skills:**
- Deep expertise in Machine Learning, Deep Learning, and Generative AI concepts.
- Proficiency in Python and SQL; experience with TensorFlow, PyTorch, scikit‑learn.
- Hands‑on with cloud AI platforms (Azure, AWS, GCP) and MLOps tools.
- Experience with data engineering/ETL tools such as Spark, Informatica, or DataStage.
- Knowledge of APIs, microservices, containers, and orchestration (e.g., Docker, Kubernetes).
- Strong grasp of enterprise architecture principles and AI governance, model risk, and regulatory compliance.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- 8+ years in data, analytics, or platform architecture roles; 4+ years designing and deploying AI/ML solutions at scale.
- Certifications in cloud architecture, AI/ML, or data platforms are a plus.
Pennington, United states
Hybrid
Senior
26-03-2026