Artificial Intelligence/Machine Learning Architect

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 ecosystem.

Key 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 explainability.

Required 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 challenges.

Preferred 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