Job Summary
We are looking for a motivated and detail-oriented IT Analyst Intern to support our technology team in maintaining and improving internal systems and digital platforms. The intern will assist with system monitoring, data analysis, troubleshooting technical issues, and supporting ongoing technology projects across the organization.
IT Systems Support
- Assist in monitoring and maintaining internal IT systems and applications.
- Support troubleshooting of hardware, software, and network-related issues.
- Help document system processes, configurations, and technical procedures.Assist in managing user accounts and system access where required.
Data & Technology Analysis
- Support the analysis of system performance and operational data.
- Assist in identifying areas for process improvement and system optimization.
- Help prepare reports and dashboards on system usage and performance.
Technical Operations
- Support the maintenance of databases, cloud systems, and internal platforms.
- Assist with system testing and deployment of updates or new features.
- Help monitor system stability, performance, and security alerts.
Project Support
- Assist the IT team in implementing ongoing technology projects.
- Help track project tasks, timelines, and deliverables.
- Provide support during system upgrades, integrations, and new implementations.
Collaboration
- Work closely with different departments to understand their technology needs.
- Support the IT team in resolving technical issues and improving system efficiency.
- Participate in team meetings and contribute ideas for process improvements.
Qualifications
- Currently pursuing or recently completed a degree in Computer Science, Information Technology, Engineering, or a related field.
- Basic understanding of IT systems, databases, and networking concepts.
- Familiarity with Microsoft Office tools and basic data analysis.
- Strong analytical, problem-solving, and organizational skills.
- Good communication skills and ability to work in a team environment.
- Willingness to learn and adapt in a fast-paced environment.
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Role Overview:
We are seeking a Data Systems & AI Insights Engineer to own our data infrastructure and analytics pipelines that power AI models. This hybrid role combines data engineering (ensuring clean, structured, and accessible datasets) with data science (model evaluation, feature engineering, performance analytics). You will work closely with the AI engineering team to provide the high-quality data needed for effective AI solutions.
Key Responsibilities:
- Design, build, and maintain data pipelines for AI/ML training and inference.
- Clean, normalize, and structure large datasets from multiple sources.
- Create datasets for supervised/unsupervised learning tasks.
- Perform exploratory data analysis (EDA) to identify patterns and insights.
- Collaborate with AI engineers to create features that improve model performance.
- Build dashboards and reporting tools to monitor AI system outputs.
- Ensure data quality, security, and compliance with regulations.
Requirements:
Strong SQL and Python skills for data manipulation and automation.Experience with data engineering tools (Airflow, dbt, Kafka, Spark, etc.).Hands-on experience with cloud data platforms (AWS Redshift, BigQuery, Snowflake, etc.).Familiarity with data science workflows (pandas, NumPy, scikit-learn, visualization libraries).Knowledge of data quality and validation best practices.Experience building ETL/ELT pipelines.Experience working with AI/ML datasets (computer vision, NLP, tabular).Familiarity with ML model evaluation metrics and experimentation.
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Role Overview:
As our AI Engineer, you will own the design, development, and deployment of AI models within our applications. You will work closely with the team to transform business requirements into production-ready AI solutions, leveraging both custom models and third-party APIs. You’ll also be responsible for setting up and managing robust MLOps pipelines to ensure continuous improvement and scalability of AI systems.
Key Responsibilities:
- Build, fine-tune, and deploy AI/ML models (NLP, CV, LLMs, or domain-specific).
- Integrate AI into existing and new application backends.
- Develop and maintain MLOps pipelines for training, deployment, and monitoring.
- Optimize AI features for latency, scalability, and cost-efficiency.
- Collaborate with data specialists and product team to ensure models are trained on high-quality datasets.
- Track model performance and iterate based on feedback and metrics.
Requirements:
- Proven experience as an ML Engineer or AI Engineer, with production-level deployments.
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face).
- Experience with LLMs (fine-tuning, prompt engineering, embeddings).
- Familiarity with MLOps tools (MLflow, Kubeflow, AWS Sagemaker, Azure ML, GCP Vertex AI).
- Experience integrating AI into APIs or full-stack applications.
- Strong understanding of cloud environments and containerization (Docker, Kubernetes).
- Experience with vector databases (Pinecone, Weaviate, Milvus).
- Experience with reinforcement learning or multi-modal AI models.
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