The Senior Cloud Backend Engineer will create AI products across various cloud platforms, leveraging strong skills in Python and cloud technologies. Responsibilities include designing and building cloud architectures, implementing data-centric products, and collaborating with DevOps practices and front-end teams.

Mechanized AI seeks a Senior Cloud Backend Engineer with over 4 years of experience to create AI products across Azure, GCP, and AWS. Responsibilities include designing cloud architectures, working with Python and Flask, and utilizing Infrastructure as Code tools like Pulumi and Terraform. The role requires collaboration with front-end teams and experience in machine learning projects in production.

The Senior Cloud Backend Engineer will develop AI products across cloud platforms like Azure, GCP, and AWS. Responsibilities include designing cloud architectures, building data-centric solutions using Python and Flask, and managing multi-tenant platforms. The role also involves engaging with front-end teams and leveraging DevOps practices.

The Senior Cloud Backend Engineer will create AI products on cloud platforms, utilizing extensive experience in Python and cloud technologies. Responsibilities include designing and building data-centric cloud architectures, implementing Infrastructure as Code, collaborating with front-end teams, and leveraging best practices in DevOps.

As a Senior Cloud Backend Engineer, you will develop AI products on cloud platforms, focus on data-centric solutions, and build cloud architectures. Responsibilities include working with Python, Flask, and various cloud services while collaborating with front-end teams and utilizing DevOps practices.

The AI Engineer will enhance the Mechanized AI platform, design ML systems, implement algorithms, perform statistical analyses, and stay updated with AI advancements. The role requires collaboration on client projects, effective communication, and strong ML expertise.

The AI Engineer will enhance the Mechanized AI platform, design ML systems, conduct experiments, and implement ML algorithms. Responsibilities include serving as the ML Subject Matter Expert, performing statistical analysis, training models, and staying updated on emerging ML technologies. Strong communication skills and a collaborative approach are essential.

The AI Engineer will develop and enhance the Mechanized AI platform, serve as a machine learning subject matter expert on client projects, design ML systems, implement algorithms, run tests, train models, and stay abreast of technology advancements. The role demands experience in various ML frameworks and excellent communication skills.

As an AI Engineer, you will develop and enhance AI platforms, contribute to machine learning solutions, and apply statistical analysis. You'll design ML systems, run tests, and keep up with industry trends, effectively communicating with clients and delivering solutions.

The AI Engineer will enhance the Mechanized AI platform by designing and building ML systems, conducting tests and experiments, and maintaining ML algorithms. The role requires expertise in client engagement, familiarity with advanced ML frameworks, and an understanding of emerging AI technologies.

The AI Engineer will enhance Mechanized AI's platform, focusing on machine learning system design, implementation of ML algorithms, statistical analysis, and model training. Responsibilities include client project support, extending ML libraries, and staying updated on ML best practices.

The AI Engineer will design and enhance AI platforms, implement machine learning algorithms, and manage client projects. Responsibilities include running ML tests, statistical analysis, and remaining updated with emerging technologies while delivering innovative solutions.

The AI Engineer will enhance the Mechanized AI platform and AI-enabled products, design ML systems, implement ML algorithms, run experiments, and stay updated with ML best practices. They will work on client projects and lead the technical delivery of machine learning solutions.

The AI Engineer will enhance the Mechanized AI platform by designing ML systems, selecting datasets, running experiments, and extending ML libraries. Responsibilities include contributing to client projects, researching ML tools, and staying updated on AI advancements. The ideal candidate has strong communication skills and at least four years of ML experience, preferably in a start-up or enterprise setting.

As an AI Engineer, you will enhance our Mechanized AI platform and products, design ML systems, research appropriate algorithms, run tests, and ensure continuous improvement in methodologies and tools. You will also contribute expertise in client projects and stay updated with AI advancements.

The AI Engineer will build and enhance the Mechanized AI platform, design ML systems, implement ML algorithms, and perform statistical analyses. The role involves client delivery, training models, and staying updated with ML best practices. Strong communication skills and experience with ML frameworks are essential.

As an AI Engineer, you will enhance the Mechanized AI platform, design ML systems, implement ML algorithms, conduct statistical analyses and manage models. You will also stay abreast of new technologies and contribute to client projects as an ML Subject Matter Expert.

As the AI Engineering Manager, you will lead the AI/ML Data Engineering team, manage AI product lifecycles, drive solution development, oversee project timelines, and foster team collaboration. You will also mentor talent, manage stakeholder expectations, and communicate progress transparently across teams.

The AI Engineering Manager will lead the AI/ML Data Engineering team, driving AI solution development and overseeing technical design and project timelines. Responsibilities include mentoring team members, implementing Agile methodologies, managing product lifecycles, and ensuring alignment with business objectives while fostering innovation and collaboration across teams.

The AI Engineering Manager will lead the AI/ML Data Engineering team, drive AI solution development, manage product lifecycles, and ensure collaboration across teams while mentoring talent. Responsibilities include overseeing project timelines, fostering a high-performing environment, and maintaining strategic alignment with business objectives.