AI/ML and MLOps Field Engineer - Remote

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Overview

The AI/ML and MLOps Field Engineer at Get It Recruit - Information Technology plays a crucial role in bridging the gap between artificial intelligence projects and operational excellence. This position entails collaborating with engineering teams to deploy and maintain machine learning models, ensuring their scalability, performance, and reliability. The Field Engineer will be responsible for executing field trials, troubleshooting technical issues, and providing insights that contribute to the continuous improvement of AI implementations. This remote opportunity requires a blend of technical expertise and effective communication skills to foster collaboration among diverse teams.

Job Responsibilities

• Collaborate with cross-functional teams to design, develop, and implement machine learning models in production.
• Monitor and analyze the performance of machine learning systems and recommend improvements as needed.
• Facilitate the deployment and operationalization of AI models using best practices in MLOps.
• Conduct field trials, gather feedback, and adjust models based on performance outcomes.
• Provide technical support and documentation for AI initiatives, ensuring all team members are informed of updates and advancements.
• Troubleshoot production issues, performing root cause analysis and implementing the necessary fixes.
• Educate and train team members and clients on AI/ML tools and models.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• Proven experience (3+ years) in machine learning engineering, data science, or a related field.
• Extensive knowledge of MLOps practices and tools (e.g., Kubernetes, Docker, MLflow).
• Proficiency in programming languages such as Python, R, or Java.
• Strong understanding of algorithms and data processing techniques.
• Experience with cloud services (AWS, Azure, GCP) and their AI/ML offerings.
• Effective communication skills, with the ability to convey complex technical concepts to non-technical audiences.

Technologies & Tools

The AI/ML and MLOps Field Engineer will engage with a diverse range of technologies and tools pivotal for successful AI implementations. This includes programming frameworks such as TensorFlow and PyTorch for machine learning model development, containerization tools like Docker and orchestration platforms such as Kubernetes for deployment, and CI/CD pipelines and version control systems for efficient production management. Familiarity with cloud environments (AWS, Azure, GCP) and data storage solutions (SQL, NoSQL) is also critical for optimal data handling and model scaling.

Ideal Candidates

Ideal candidates for the AI/ML and MLOps Field Engineer position should possess a strong analytical mindset combined with problem-solving skills to effectively address technical challenges. They should be self-motivated, capable of working independently in a remote setting, and demonstrate a commitment to continuous learning and innovation in the rapidly evolving field of AI and MLOps. Strong interpersonal skills are essential, as the role involves collaboration with various teams and stakeholders, both technical and non-technical. A proactive, detail-oriented approach is pivotal for ensuring successful execution and operational efficiency in AI projects.