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Design and implement machine learning models; perform exploratory data analysis; collaborate with stakeholders; deploy and monitor models; mentor junior team members.

Lead a team of data scientists, architect machine learning solutions, conduct research, and communicate insights to stakeholders. Enhance team skills and propose data-driven innovations.

As a Machine Learning Engineer, you will develop ML models, optimize performance, implement client requirements, and collaborate on technical solutions.

Lead the Machine Learning team, oversee project development, optimize ML systems and data pipelines, mentor team members, and align technical and business goals.

The Machine Learning Engineer Specialist will design, build, and maintain recommendation systems, improve personalization, and manage ML pipelines while collaborating with stakeholders to deliver scalable solutions.

The DevOps role focuses on infrastructure automation, Kubernetes operations, and managing production-grade cloud infrastructure on AWS, using Terraform. Responsibilities include building CI/CD pipelines, improving observability, and collaborating with architecture teams to meet security standards.

As a Data Engineer Lead, you will develop batch and streaming data pipelines, maintain data contracts, guide teams on data modeling, and mentor engineers.

As a Senior Data Engineer, you will develop batch and streaming data pipelines, maintain data contracts, and guide domain teams on data modeling, while mentoring other engineers.

As a Data Engineer Lead, you'll lead data projects, design ETL processes, mentor team members, and collaborate with clients to deliver custom solutions.

The Data Developer will implement data pipelines, research new tools, and collaborate with teams for smooth integration of data systems.