MLOps Engineer

About the employer:

The client is an IT services provider specializing in software development, IT consulting, and digital transformation. It helps businesses improve operations and customer experiences through custom solutions, cloud services, and data analytics.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s/PhD a plus),

• experience in Machine Learning, AI Engineering, or MLOps, including production deployments of ML or GenAI systems,

• expert-level Python skills with deep understanding of its data science and ML ecosystem (NumPy, Pandas, PyTorch, TensorFlow, etc.),

• proven experience designing and implementing cloud-based ML solutions, ideally on AWS (SageMaker, IAM, networking, compute, storage),

• hands-on experience with MLflow, GitLab CI/CD, and infrastructure as code tools such as Terraform,

• familiarity with monitoring and observability tools (e.g., Prometheus, Grafana, Evidently AI),

• experience with RAG (Retrieval-Augmented Generation) or agentic AI solutions is a strong plus,

• strong understanding of MLOps principles, CI/CD pipelines, and scalable ML infrastructure,

• excellent communication skills with the ability to explain complex architectures and collaborate with diverse technical and business stakeholders.,

• demonstrated experience mentoring and guiding technical teams,

• strong problem-solving abilities, ownership mindset, and a collaborative approach to teamwork.

Responsibilities:

• design, document, and develop scalable AI OR ML architectures on AWS,

• build, deploy, and maintain production-grade ML and GenAI systems using best practices in AI engineering and MLOps,

• collaborate closely with users and stakeholders to translate business requirements into technical solutions and deliver impactful AI applications,

• support teams with architecture design, onboarding, production deployment, refactoring, and continuous improvement,

• manage the end-to-end MLOps lifecycle using tools such as MLflow, GitLab CI/CD, and AWS-native services,

• contribute to the AI platform roadmap with a strong user-centric mindset and focus on scalability and reliability,

• mentor and guide data scientists, data engineers, and MLOps engineers in best practices for ML systems development and operations.

Our client offers:

• B2B contract,

• full remote model of work.