Artificial Intelligence/Machine Learning Architect
4 weeks ago
The Role :
This is a highly strategic role for an individual with over 15 years of technical experience in designing, building, and scaling complex, enterprise-level AI/ML systems.
You will be the technical beacon, responsible for defining the architectural direction and ensuring our AI/ML strategy aligns seamlessly with our business goals.
You will provide technical mentorship to a team of data scientists and ML engineers, ensuring the robustness, scalability, and security of our entire technology Responsibilities :
- Propose and lead the adoption of new technologies and methodologies to stay ahead of industry trends in machine learning.
- ML System Design & Governance : Design and govern highly scalable, reliable, and performant systems for data ingestion, feature engineering, model training, and serving.
- This includes defining MLOps pipelines and ensuring model governance.
- Technical Leadership & Mentorship : Act as a technical expert and hands-on leader, mentoring and guiding data scientists and ML engineers.
- Foster a culture of technical excellence and help the team solve the most complex AI/ML challenges.
- Cross-Functional Collaboration : Work closely with product management, business stakeholders, data science teams, and engineering teams to translate business requirements into viable, production-ready AI/ML solutions.
- Innovation & Research : Stay current with emerging AI/ML technologies and research, evaluate their potential impact, and lead proof-of-concept projects to validate new algorithms, frameworks, and architectural patterns.
- Quality & Reliability : Ensure non-functional requirements such as security, reliability, scalability, and maintainability are built into the AI/ML architecture.
- Implement systems for continuous model monitoring, drift detection, and Qualifications :
- 15+ years of total experience in software development, with a minimum of 5- 7 years in a dedicated Software Architect or Principal Engineer role focused on AI/ML or data-intensive systems.
- Proven experience in designing and implementing large-scale, distributed machine learning systems, data pipelines, and MLOps architectures.
- Expertise in at least one major cloud platform (AWS, Azure, or GCP), with strong hands-on experience in
their respective AI/ML services (e.g., AWS SageMaker, GCP Vertex AI, Azure Machine Learning).
- Deep knowledge of machine learning algorithms, statistical modeling, and system design patterns for AI/ML.
- Exceptional communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
- Strong leadership and problem-solving skills, with a track record of successfully leading engineering teams through major technical Qualifications :
- Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC.
- Relevant professional certifications (e.g., AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer).
- Active participation in the open-source community, blogs, or technical conferences
(ref:hirist.tech)
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