- Company Name
- Automat-it
- Job Title
- Senior AI/ML Architect
- Job Description
-
**Job Title:** Senior AI/ML Architect
**Role Summary:**
Architect and deliver end‑to‑end AI/ML solutions for high‑growth startups, spanning classical machine learning, deep learning, and generative AI. Lead technical design, proposal development, and customer workshops while driving production deployments on AWS. Act as a trusted advisor to C‑level executives, data scientists, and engineering teams, ensuring scalable, maintainable, and high‑impact AI systems.
**Expectations:**
- Design and implement production‑ready ML pipelines and LLM serving infrastructure.
- Translate business objectives into robust, scalable ML architectures.
- Own end‑to‑end solution delivery from concept through production and continuous improvement.
- Engage customers in workshops, POCs, and architecture reviews; provide ongoing technical guidance.
- Keep abreast of emerging ML/AI trends and integrate best practices into internal enablement.
- Travel locally and internationally (quarterly) to support client engagements and partner events.
**Key Responsibilities:**
- Design end‑to‑end ML solutions: classical models, deep learning, generative AI, and LLM applications.
- Create technical proposals, reference architectures, and deployment plans for AWS environments.
- Lead workshops, proofs of concept, and architecture reviews with startup customers.
- Develop and maintain distributed training workflows (Horovod, Ray, etc.) and LLM serving stacks.
- Build MLOps pipelines for model tracking, versioning, monitoring, and automated deployment.
- Provide technical leadership and mentorship to customers and internal teams.
- Deliver presentations and documentation for stakeholders and senior leadership.
- Participate in continuous improvement initiatives and knowledge sharing across the organization.
**Required Skills:**
- 7+ years of software engineering, data science, or ML experience.
- 3+ years of deploying ML solutions in production environments.
- Hands‑on proficiency with AWS ML services (SageMaker, Bedrock, etc.).
- Experience with distributed training frameworks (Horovod, Ray).
- Strong background in generative AI and large language model (LLM) development.
- Advanced Python programming and deep‑learning frameworks (PyTorch, TensorFlow).
- MLOps expertise: pipelines, model versioning, monitoring, and CI/CD.
- Familiarity with Docker, Kubernetes, Terraform.
- Excellent communication, customer‑facing, and stakeholder‑management skills.
- Ability to work independently in a fast‑paced, hybrid environment.
**Required Education & Certifications:**
- Master’s degree in Computer Science, Machine Learning, Data Science, or related field (advantage).
- AWS Certified ML Specialty or AWS Certified Solutions Architect – Professional (advantage).
- Additional certifications in Kubernetes, FinOps, or related disciplines are a plus.