HappieHire
Website:
happiehire.com
Job details:
Position Title: SLM Data Science Lead - Architect – AI/ML
Department: Engineering & Technology
Function: AI/ML Platform Engineering
Role Summary
The Principal Data Scientist / SLM Model Development Architect is a senior technical leadership role responsible for defining the architecture, strategy, and enterprise adoption of Small Language Models (SLMs) and advanced AI solutions. This role provides end-to-end ownership of model design, optimization, deployment, and governance while mentoring teams and influencing AI strategy across the organization.
Responsibilities
Architecture & Strategy
- Define and own the enterprise architecture, standards, and roadmap for Small Language Model (SLM) development.
- Design domain-specific SLMs optimized for accuracy, latency, cost, and scalability.
- Drive architectural decisions for model selection, fine-tuning, compression, and inference optimization.
- Ensure alignment of AI solutions with enterprise security, compliance, and governance requirements.
Advanced Model Development
- Lead the design, development, and deployment of ML, DL, and SLM-based solutions.
- Apply deep mathematical and statistical knowledge to optimize model performance.
- Demonstrate successful delivery of multiple production deployments with measurable business impact.
- Provide architectural oversight for traditional ML, deep learning, and NLP-based systems.
NLP & Language Modeling
- Architect and guide solutions involving NLP, embeddings, transformers, and language models.
- Lead fine-tuning and adaptation of language models for domain-specific use cases.
- Establish best practices for prompt engineering, evaluation metrics, and performance monitoring.
Technical & Platform Leadership
- Provide technical authority in Python, scientific computing, and data processing frameworks.
- Guide teams on the effective use of TensorFlow, PyTorch, and Keras.
- Ensure high-quality analytical data access through complex and optimized SQL designs.
- Oversee development in Linux and GPU-based environments.
Cloud, MLOps & Production Readiness
- Architect and govern ML/AI solutions on AWS or Azure platforms.
- Define and enforce MLOps standards, including CI/CD, model versioning, monitoring, and lifecycle management.
- Ensure reliability, scalability, and maintainability of AI systems in production.
Leadership & Mentorship
- Act as Principal Architect and technical mentor for Data Scientists and ML Engineers.
- Lead design reviews, technical decision forums, and architectural governance boards.
- Collaborate closely with product, engineering, security, and compliance stakeholders.
- Drive innovation while ensuring delivery discipline in Agile environments.
Required Skills & Expertise
- Strong foundation in ML algorithms: Random Forest, SVM, Regression models, Boosting & Bagging
- Deep learning expertise: CNN, RNN, LSTM, GRU
- Advanced NLP and language model experience
- Expert-level Python programming
- Cloud-based ML architecture and deployment
- Enterprise AI governance and best practices
Preferred / Nice to Have
- Experience with Computer Vision cases
- Exposure to Responsible AI, model risk management, and regulatory compliance
- Experience defining AI strategy at an organizational or platform level
Role Level
- Principal / Architect
- Individual Contributor with enterprise-level technical leadership responsibilities
Experience
- 8 - 12 years of experience in Data Science, Machine Learning, and Deep Learning
- Proven experience in architecting and deploying production-grade AI/ML systems at enterprise scale
Educational Qualification
- ME / BE / MCA / PhD
- PhD preferred for advanced research and architectural leadership roles
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