Mlops Engineer

Who you are

You are a skilled MLOps Engineer with a strong background in managing the operational lifecycle of machine learning systems. You have experience with both traditional machine learning and emerging generative AI applications, and you thrive in environments that allow you to shape your work and craft. Your curiosity drives you to solve complex problems and build scalable solutions.

You possess a deep understanding of infrastructure, automation, quality, and reliability engineering. Your expertise enables you to implement scalable training, evaluation, deployment, and monitoring processes for a wide range of ML and GenAI workloads. You are adept at managing model upgrades, framework versions, and regression testing, ensuring performance across systems and solutions.

What you'll do

In this role, you will support the full operational lifecycle of machine learning systems, focusing on both traditional and generative AI applications. You will collaborate with the Data Science team to build products powered by AI, contributing to the design and implementation of scalable infrastructure. Your responsibilities will include automating processes, ensuring quality and reliability, and monitoring performance across various ML workloads.

You will be involved in managing model upgrades and framework versions, conducting regression testing, and performing maintenance tasks to ensure optimal performance. Your work will directly impact the efficiency and effectiveness of the AI products developed by Achievers, allowing you to make a significant contribution to the team.

What we offer

Achievers provides a dynamic work environment where you can grow your skills and make a real impact. You will have the opportunity to work with a motivated team that values curiosity and innovation. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse perspectives lead to better solutions. Join us in shaping the future of AI-powered products.