MLOps Professional Services Engineer (Cloud & AI Infra)

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Position Overview

The MLOps Professional Services Engineer (Cloud & AI Infra) at Lavendo will play a critical role in bridging the gap between machine learning development and operationalization. This position focuses on deploying, managing, and optimizing AI solutions in cloud environments while ensuring that best practices in MLOps are adhered to. The MLOps engineer will work closely with engineering teams and clients to ensure the scalable and reliable performance of machine learning models across various platforms, contributing significantly to the success of AI initiatives within the organization.

Job Responsibilities

• Design, deploy and maintain MLOps pipelines to automate model training, validation, and deployment processes.
• Collaborate with data scientists and software engineers to integrate machine learning models into production systems.
• Monitor and troubleshoot machine learning workflows to ensure smooth operation and performance optimality.
• Implement best practices for version control, testing, and security for AI models in cloud environments.
• Conduct performance tuning of machine learning algorithms and workflows in cloud infrastructure.
• Provide technical guidance and support to clients during the deployment of AI solutions.
• Stay current with industry trends in MLOps and suggest improvements or new strategies for Lavendo’s solutions.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; a Master’s degree is preferred.
• 3+ years of experience in MLOps or relevant experience in machine learning and software development.
• Proficiency in programming languages such as Python and frameworks like TensorFlow or PyTorch.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization tools like Docker and orchestration platforms like Kubernetes.
• Strong knowledge of machine learning concepts, algorithms, and data preprocessing techniques.
• Excellent problem-solving skills with the ability to work in a fast-paced, collaborative environment.

Technologies & Tools

The MLOps Professional Services Engineer will predominantly utilize a range of technologies and tools including, but not limited to, Python, TensorFlow, PyTorch, cloud platforms (AWS, Azure, Google Cloud), Docker, Kubernetes, MLflow, and Jupyter Notebooks. Familiarity with CI/CD tools and monitoring solutions will also be essential in ensuring seamless operations and deployments of machine learning models in production.

Ideal Candidates

The ideal candidates for the MLOps Professional Services Engineer role will possess strong analytical and critical thinking skills, conversant in both technical and business aspects of machine learning applications. They should exhibit excellent communication skills to effectively convey complex concepts to clients and internal teams alike. A proactive mindset, adaptability to new technologies, and a genuine passion for driving innovation in AI and machine learning will be key traits for success in this position at Lavendo.