Applied AI Engineer – Level II

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360 Social Agency

11 - 50 employees

Founded 2018

🛍️ eCommerce

🤝 B2B

eCommerce • Digital Marketing • B2B

360 Social Agency is a premier digital marketing agency that specializes in creating personalized and effective marketing strategies for businesses. With a proven track record of delivering rapid results, they offer a 30-day action plan designed to align with company objectives and drive growth. Their extensive services include SEO, social media marketing, advertising, e-commerce solutions, and graphic design, leveraging cutting-edge tools and expert marketing talent to maximize performance and achieve genuine success for their clients.

📋 Description

• Collaborate with experienced data scientists and software engineers to gain insights into building scalable and efficient data pipelines, model training, and deployment systems. • Troubleshoot issues in the entire machine learning infrastructure, from Linux, Docker, and Kubernetes up to the highest levels of our ML stack. Resolve issues, improve system performance, and make our stack the best in the industry. • Assist in the design and development of on-premises MLOps solutions to support the delivery of machine learning models, and a seamless handover between research and productionization of ML artifacts. • Drive and uphold high engineering standards, bringing consistency to codebases encountered and ensuring software is adequately reviewed, tested, and integrated. • Optimize existing models for better performance and throughput. • Incorporate ML model training, validation, and evaluation settings in addition to traditional coding tests like unit and integration testing. • Build and maintain tools for deployment, monitoring, and operations. - Continuously refine and enhance CI/CD workflows to support the evolving needs of the machine learning infrastructure.

🎯 Requirements

• 3+ years of experience in MLOps or full stack Machine Learning - Good programming skills in a modern programming language (Python, Scientific Python Stack, Cuda). • Understanding of the MLOps life cycle and experience with MLOps workflows. • Experience with tools & practices of the trade, such as Kubernetes, GCP/AWS/Azure, CI/CD, common ML frameworks, and data management. • A keen interest in machine learning engineering and a willingness to explore how it can be scaled effectively. • Strong desire to learn and good communication skills, with an enthusiasm for collaborative problem-solving.

🏖️ Benefits

• Competitive salary and annual bonus • Medical coverage • Life and accidental insurance • Vacation & leaves of absence (menstrual, flexible, special, and more!) • Developmental opportunities through education & developmental reimbursements & professional workshops • Maternity & parental leave • Hybrid & remote model with flexible working hours • On-site & remote company events throughout the year • Tech & WFH stipends & new hire allowances • Employee referral program • Premium access to Quillbot

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