Highlights
Hands-on experience with ML models, LLM APIs, and real-world data pipelines. Collaborate on cutting-edge AI projects.
Description
Job Summary
pJoin our dynamic Data & AI team as a curious and motivated entry-level analyst/engineer. This role involves working on real-world data pipelines, building and evaluating machine learning models, and deploying intelligent agentic workflows using modern LLM tooling. Ideal for fresh graduates or early-career professionals passionate about artificial intelligence.
Responsibilities
- Collect, clean, and transform structured/unstructured data for analysis and model training.
- Build and fine-tune ML models (classification, regression, clustering, NLP) using Python.
- Develop and test agentic AI workflows using LLM APIs with tool use, memory, and planning.
- Integrate agents with external tools using MCP or function calling.
- Create PowerBI dashboards, visualisations, and reports to communicate insights to stakeholders.
- Evaluate and benchmark LLM outputs; implement prompt engineering and RAG pipelines.
- Assist in deploying models and agentic applications to Azure cloud or on-premise environments.
- Collaborate with cross-functional teams to understand business requirements and deliver AI-driven solutions.
Required Skills
- Data Cleaning
- Python Programming
- Machine Learning Models
- LLM APIs
- Dashboard Visualization
Required Skills Explained
- Python programming for data manipulation and machine learning model building.
- Experience with LLM APIs like Claude, GPT-4o, Gemini for developing AI workflows.
- Data collection, cleaning, and transformation techniques for analysis.
- Understanding of ML models such as classification, regression, clustering, and NLP.
- Proficiency in creating PowerBI dashboards and visualizations.
- Knowledge of Azure cloud or on-premise deployment environments.
Who is this for
pThis role is ideal for individuals who are curious, motivated, and passionate about AI. Fresh graduates or early-career professionals with a strong interest in data science and machine learning will find this position fulfilling.
Why This Job is a Good Opportunity
ulliHands-on experience with real-world data pipelines and AI models.liPotential to work with cutting-edge LLM technologies in a fast-paced environment.liOpportunity for collaboration across different teams, gaining diverse skill sets.liCompetitive salary and benefits package suitable for early-career professionals.
Interview Preparation Tips
- Prepare examples of projects you have worked on using Python and ML libraries.
- Discuss your understanding of LLMs and their applications in AI workflows.
- Showcase your ability to clean and transform complex datasets.
- Create a mock PowerBI dashboard or visualization to demonstrate your skills.
Career Growth in This Role
pThis role provides ample opportunity for career advancement. As you gain experience, you can take on more responsibility in model development, workflow integration, and deployment. The company encourages internal growth, so there are opportunities to move into senior roles or specialize further in AI engineering.pWith additional certifications like Azure Data Analytics and ML Specialty, your skills will be even more valuable. Continued learning in areas like prompt engineering and RAG pipelines can also open up new career paths within the tech industry.
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Skills
Frequently Asked Questions
What certifications are preferred?Relevant certifications such as Azure Data Analytics, ML Specialty, or DeepLearning.AI are a strong plus.
Is there any specific software I need to be proficient in?Proficiency in Python and experience with data cleaning and visualization tools is essential.
What kind of projects can I expect to work on?You will work on real-world data pipelines, build ML models, and develop AI workflows using LLM APIs.
