Job Description

Our Client a global tech firm is seeking an AI Engineer to join their team in in Cape town or anywhere in SA on a contract basis. They offer stability, growth, attractive rates and a great working environment.
More about the project: The problem we are trying to solve is to fast trach AI / GenAI in our organisation by building a set of lighthouse Use Cases that showcase delivering value in AI.
Solution/Deliverable:
There are multiple projects focusing on building AI/GenAI Use Cases. Its green fields development initially building the first use cases in our new Generative AI architectures.
Attractive tech exposure:
Generative AI Technologies: LangChain, AWS Bedrock, MLFlow, Vector databases
Mandatory:

• 5-8 years of experience as AI Developer with experience/exposure to Databricks Platform
• Building/running AI Systems, developing and training machine learning models, Building AI pipelines,
• Integrating AI capabilities into applications, optimizing algorithms for efficiency & scalability.
• Machine Learning 6-8 years
• AI Engineer 6-8 years

Responsibilities:

• Designs, develops, and implements artificial intelligence systems to solve complex real-world problems and enhance business processes.
• AI Engineers leverage cutting-edge technologies to build systems capable of decision-making, automation, and advanced data analysis.
• Building/running AI Systems, developing and training machine learning models, building AI pipelines, integrating AI capabilities into applications, optimizing algorithms for efficiency and scalability, and ensuring the ethical deployment of AI solutions.
• Proficiency in programming languages like Python, knowledge of AI frameworks such as TensorFlow or PyTorch, and expertise in data preprocessing, neural networks, and cloud platforms are essential.
• Managing big data systems, deploying AI models into production, and working with tools for monitoring and maintaining AI systems post-deployment.
• Strong problem-solving skills, a deep understanding of emerging AI technologies, and the ability to collaborate with cross-functional teams are vital traits for success in this role.

AI Frameworks/Systems/Technologies

• Prompt engineering
• LangChain
• LlamaIndex
• CrewAI
• Ollama
• RAG
• Agents
• React/Angular
• TensorFlow/PyTorch
• Natural Language Processing (NLP) frameworks
• Computer Vision libraries (e.g., OpenCV, YOLO)
• Recommendation engines
• MS Presidio

Data Science

• Python (NumPy, Pandas, Scikit-learn)

• R

• Jupyter Notebooks

• Tableau/Power BI

• SQL

• Apache Spark (for analysis)

Data Engineering

• Apache Kafka
• Apache Airflow
• Hadoop
• Snowflake
• Google BigQuery
• AWS Glue
• ETL Tools (Talend, Informatica)
• Spark
• NoSQL Databases (MongoDB, Cassandra)
• Databricks

MLOps/Platforms

• Docker
• Kubernetes
• MLflow
• Git/GitHub for version control
• AWS Sagemaker, Bedrock, Lambda, etc.
• Databricks
• Kubeflow
• CI/CD pipelines (Azure ADO/Jenkins/CircleCI
• Prometheus/Grafana for monitoring
• Terraform/Ansible for infrastructure as code (IaC)
• Statistical modeling tools