Tech Lead Data Science

Axiata Digital Labs

Job Location:

Colombo - Sri Lanka

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Key Responsibilities

Lead the development and deployment of advanced data science and AI solutions across Machine Learning (ML) Deep Learning (DL) Generative AI and Agentic AI use cases
Lead the end-to-end model lifecycle management including data ingestion feature engineering model development evaluation deployment monitoring and retraining
Lead the development and operationalization of Generative AI and Agentic AI systems including prompt engineering orchestration frameworks tool integration and autonomous agent workflows
Collaborate with cross-functional teams (Engineering Data Engineering Product QA DevOps) to deliver robust AI-powered solutions
Provide technical leadership and mentorship to data scientists and ML engineers driving capability development and code quality standards
Ensure AI solutions comply with organizational governance frameworks including security privacy ethical AI and regulatory requirements
Evaluate and integrate modern AI/ML tools frameworks and platforms (e.g. model serving frameworks vector databases orchestration tools)
Translate complex business problems into scalable AI solutions and communicate outcomes effectively to stakeholders and leadership

Person Specifications

Bachelors degree in IT Computer Science Software Engineering Data Science Engineering Mathematics or a related field
68 years of professional experience in Data Science AI or ML working in production-grade environments

Technical Expertise

Strong hands-on experience in Machine Learning and Deep Learning (supervised/unsupervised learning NLP computer vision)
Practical experience in Generative AI (LLMs prompt engineering RAG pipelines embeddings fine-tuning)
Experience designing and implementing Agentic AI systems (multiagent orchestration tool usage autonomous workflows)
Solid knowledge of MLOps practices (model lifecycle management CI/CD monitoring retraining pipelines)
Experience in LLMOps (prompt/version management evaluation frameworks guardrails cost optimization observability)
Proficiency in Python and common AI/ML frameworks (e.g. TensorFlow PyTorch Scikit-learn)
Experience with cloud platforms (AWS Azure or GCP) and cloudnative platforms & services (e.g. Copilot Studio Bedrock Vertex AI Azure OpenAI)
Familiarity with data engineering concepts (ETL pipelines feature stores data lakes/warehouses)

Leadership & Soft Skills

Strong architectural thinking and problem-solving skills with the ability to design scalable AI systems
Proven ability to lead teams mentor engineers and drive delivery in fast-paced environments
Excellent communication skills with the ability to engage both technical and non-technical stakeholders
Experience working within governance frameworks (e.g. AI governance security compliance)
Strong ownership mindset with a focus on quality performance and business impact

Key Responsibilities Lead the development and deployment of advanced data science and AI solutions across Machine Learning (ML) Deep Learning (DL) Generative AI and Agentic AI use casesLead the end-to-end model lifecycle management including data ingestion feature engineering model development eval...

Key Responsibilities

Lead the development and deployment of advanced data science and AI solutions across Machine Learning (ML) Deep Learning (DL) Generative AI and Agentic AI use cases
Lead the end-to-end model lifecycle management including data ingestion feature engineering model development evaluation deployment monitoring and retraining
Lead the development and operationalization of Generative AI and Agentic AI systems including prompt engineering orchestration frameworks tool integration and autonomous agent workflows
Collaborate with cross-functional teams (Engineering Data Engineering Product QA DevOps) to deliver robust AI-powered solutions
Provide technical leadership and mentorship to data scientists and ML engineers driving capability development and code quality standards
Ensure AI solutions comply with organizational governance frameworks including security privacy ethical AI and regulatory requirements
Evaluate and integrate modern AI/ML tools frameworks and platforms (e.g. model serving frameworks vector databases orchestration tools)
Translate complex business problems into scalable AI solutions and communicate outcomes effectively to stakeholders and leadership

Person Specifications

Bachelors degree in IT Computer Science Software Engineering Data Science Engineering Mathematics or a related field
68 years of professional experience in Data Science AI or ML working in production-grade environments

Technical Expertise

Strong hands-on experience in Machine Learning and Deep Learning (supervised/unsupervised learning NLP computer vision)
Practical experience in Generative AI (LLMs prompt engineering RAG pipelines embeddings fine-tuning)
Experience designing and implementing Agentic AI systems (multiagent orchestration tool usage autonomous workflows)
Solid knowledge of MLOps practices (model lifecycle management CI/CD monitoring retraining pipelines)
Experience in LLMOps (prompt/version management evaluation frameworks guardrails cost optimization observability)
Proficiency in Python and common AI/ML frameworks (e.g. TensorFlow PyTorch Scikit-learn)
Experience with cloud platforms (AWS Azure or GCP) and cloudnative platforms & services (e.g. Copilot Studio Bedrock Vertex AI Azure OpenAI)
Familiarity with data engineering concepts (ETL pipelines feature stores data lakes/warehouses)

Leadership & Soft Skills

Strong architectural thinking and problem-solving skills with the ability to design scalable AI systems
Proven ability to lead teams mentor engineers and drive delivery in fast-paced environments
Excellent communication skills with the ability to engage both technical and non-technical stakeholders
Experience working within governance frameworks (e.g. AI governance security compliance)
Strong ownership mindset with a focus on quality performance and business impact