Senior MLOps Engineers | Ai Engineers

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 Engineers 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. This is a blank canvas and would need a strong leader to manage the ambiguity and provide structure to the team alongside also developing themselves and getting their hands dirty.

This is a career highlight job and is a very rarer opportunity.
You will be the “guy” for MLOps.

We are looking for a highly skilled AI Engineers 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.

Requirements

Key Responsibilities - MLOps:

• 
  Lead the MLOps charge 
• Be the go-to thought leader in the space providing expert guidance to all other teams 
• Create solution accelerators for various MLOps architectures across various clouds, Azure, AWS, Databricks and alternatively create solutions that optimize for accuracy, cost, and latency while following engineering best practices and creating solution architectures that are in line with the policies.
• The solution accelerators would typically be IaC via CloudFormation, Terraform, or Bicep and in combination with the various cloud SDKs.

Technical Skills:

• 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:

• 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

Who we are: