Sequertek - Data Science Architect - NLP/Generative AI

Description :

Role Overview :

We are seeking an accomplished Data Science Architect to design, build, and govern large-scale, production-grade Machine Learning and AI platforms.

This role demands deep hands-on expertise in ML, Deep Learning, NLP, and Generative AI, combined with strong software architecture, data engineering, and cloud-native system design capabilities.

The Data Science Architect will be responsible for defining end-to-end ML system architectures, ensuring scalability, security, performance, and alignment with business objectives.

The role requires close collaboration with business stakeholders, data engineers, ML engineers, and product teams while providing technical leadership and architectural governance.

Key Responsibilities :

Architecture & System Design :

Design and own the end-to-end architecture of Machine Learning and AI systems, including :

- Data ingestion and streaming

- Data preprocessing and feature engineering

- Model training, evaluation, and experimentation

- Model deployment, monitoring, and lifecycle management

- Define scalable and fault-tolerant architectures capable of handling high-volume, high-velocity, and high-variety data.

- Ensure architectural best practices around performance, reliability, security, maintainability, and cost optimization.

- Capture and document functional and non-functional requirements including scalability, latency, availability, compliance, and security.

Machine Learning & AI Leadership :

- Evaluate, select, and implement appropriate ML, Deep Learning, NLP, and Generative AI models based on data characteristics and business goals.

Provide architectural guidance for:

- Supervised, unsupervised, and reinforcement learning systems

- Large Language Models (LLMs), prompt engineering, RAG frameworks, and fine-tuning strategies

- Drive adoption of MLOps best practices, including experiment tracking, model versioning, automated retraining, and model monitoring.

Data Engineering & Big Data :

- Architect and implement robust data pipelines for collection, cleansing, transformation, and feature engineering.

- Work with large-scale distributed systems and big data platforms to ensure efficient data processing.

- Design systems for both batch and real-time streaming use cases.

DevOps, MLOps & CI/CD :

- Define and implement CI/CD pipelines for ML and data platforms using modern DevOps and MLOps tooling.

- Enable automated testing, validation, deployment, and rollback of ML models and data pipelines.

- Ensure smooth integration of ML systems into enterprise ecosystems.

Security & Compliance :

- Embed security-by-design principles across data and ML architectures.

- Collaborate with security teams to ensure compliance with enterprise security standards.

- Apply best practices for data protection, access control, model governance, and auditability.

- Preferable experience with security analytics, endpoint detection and response (EDR), managed detection and response (MDR) use cases.

Technical Leadership & Stakeholder Collaboration :

- Provide technical leadership and mentorship to data scientists, ML engineers, and developers.

- Participate in solutioning, architecture reviews, and proposal development (RFPs).

- Collaborate with product, business, engineering, and platform teams to translate business needs into scalable AI solutions.

- Promote best practices in reuse, defect prevention, automation, and productivity enhancement.

Required Qualifications :

Education :

- Bachelors or Masters degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or related fields.

Experience :

- 10+ years of overall IT experience with 4 to 5 years in an Architect role.

- 4+ years of hands-on experience applying statistical and machine learning techniques to real-world, production datasets.

- 4+ years of experience as a software developer building scalable, secure, and high-performance applications.

- 2+ years of experience independently designing core product modules or complex systems.

- Proven hands-on experience with Generative AI solutions.