Machine Learning Engineer

New Yesterday

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner. Are you a Machine Learning Engineer with expertise in Google Cloud Platform (GCP) and Vertex AI? We are looking for  two talented professionals  to join our team in a fully remote, onshore capacity. If you thrive in building and deploying scalable AI solutions, this role is for you! What You'll Do:
Collaborate with cross-functional teams to design and deploy ML models.
Develop reusable, scalable code for AI/ML applications.
Leverage GCP services to build end-to-end machine learning pipelines.
Optimize models for performance and scalability using Vertex AI. Requirements Key Requirements:
Google Cloud Platform (GCP) Experience:  Strong proficiency in GCP services, including data engineering and machine learning tools.
Google Vertex AI Expertise:  Hands-on experience with model training, deployment, and optimization using Vertex AI.
Model Development & Deployment:  Proven ability to design, build, and productionize machine learning models.
API Development:  Skilled in developing robust APIs for seamless integrations.
Python Programming with CI/CD:  Experience in Python-based applications and implementing CI/CD pipelines.
Why Join Us?
Work remotely while contributing to cutting-edge projects.
Collaborate with a dynamic team passionate about AI/ML innovation.
Opportunity to work with the latest Google Cloud technologies.
Ready to take the next step?  Apply now and be part of a team that’s shaping the future of AI! Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
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Location:
Chicago

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