DVT is a global custom software development and data engineering company. With our remote and hybrid options, our vision is to be South Africa's favourite custom software solutions & services company, with a global footprint. You will have the opportunity to work alongside some of the most established developers in the country with the latest technologies. DVT is committed to continuously training our staff and we are very proud of our culture of learning, from internal speaking and training to sponsoring a variety of technical events from DevConf to GDG.
We are seeking a highly skilled MLOps Engineer with a minimum of 5 years of experience in software engineering and a strong focus on MLOps. The ideal candidate will be responsible for creating and maintaining machine learning pipelines, setting up the full MLOps lifecycle, and working in AWS cloud environments.
We are also looking for a highly skilled AI Engineer with a strong software engineering background and extensive experience in developing and deploying AI applications. The ideal candidate will have expertise in Retrieval-Augmented Generation (RAG) applications and agent-based frameworks like CrewAI.
Key Responsibilities - MLOps:
Experiment Environments: Design and create robust environments for machine learning experiments.
ML Pipelines: Develop, deploy, and maintain scalable ML pipelines.
MLOps Lifecycle: Implement and manage the end-to-end MLOps lifecycle, ensuring seamless integration and deployment of ML models.
Cloud & Multicloud: Work extensively with cloud platforms and multicloud environments to optimize ML operations.
Technical Skills - MLOps:
Cloud Platforms: Proficiency with SageMaker, Azure ML Studio.
MLOps Tools: Experience with MLFlow, Prometheus, Grafana.
Containerization & Orchestration: Strong skills in Docker and Kubernetes.
Programming: Advanced knowledge of Python.
Frameworks: Experience with Ray, FastAPI, and Flask.
ML Algorithms: Familiarity with machine learning algorithms and frameworks such as TensorFlow or PyTorch is a plus.
Key Responsibilities - AI Engineers:
RAG Applications: Design, develop, and implement Retrieval-Augmented Generation applications.
Agent-Based Frameworks: Utilize frameworks such as CrewAI to build intelligent agent-based systems.
Software Engineering: Apply strong software engineering principles to develop robust and scalable AI solutions.
AI Pipelines: Create and maintain AI pipelines using modern tools and frameworks.
Cloud Integration: Deploy and manage AI solutions on cloud platforms, including Bedrocks and Azure AI Studio.
Technical Skills - AI Engineers:
Programming: Proficiency in Python.
Web Frameworks: Experience with FastAPI and Flask.
AI Tools: Knowledge of LangChain, LlamaIndex, Chroma, Weaviate, and Qdrant.
Cloud Platforms: Experience with AI on Cloud, Bedrocks, and Azure AI Studio.
Qualifications:
Experience: Proven experience with RAG applications and agent-based frameworks.
Software Engineering: Strong background in software engineering is non-negotiable.
Preferred Skills:
Frameworks: Familiarity with CrewAI and similar agent-based frameworks.
AI Tools: Experience with LangChain, LlamaIndex, Chroma, Weaviate, and Qdrant.
Soft Skills:
Strong analytical and problem-solving abilities.
Excellent communication and collaboration skills.
Ability to work in a dynamic and fast-paced environment.
Interview Process:
Recruiter call
Online Assessment / Take Home assessment
Technical Interview
Decision & Feedback
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