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Lead Machine Learning Engineer

Datatonic

🌍 North America 🏠 Remote ⏱ Part-time 💼 Senior 🗓 1 weeks ago

SHAPE THE FUTURE OF AI & DATA WITH US

At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.

YOUR MISSION

As a Lead ML Engineer, you will be responsible for overseeing and guiding a growing team of Engineers, specializing in Machine Learning Engineering and Data Science.

As the Team Lead, you will play a crucial role in ensuring the successful delivery of innovative solutions, fostering a collaborative and high-performance team environment, and driving the technical direction of projects.

This is an excellent opportunity for someone who thrives in a dynamic, fast-paced setting and is eager to contribute to the success of both the team and the organization.

WHAT YOU’LL DO

TEAM LEADERSHIP:

- Provide strategic and technical leadership to the ML team, ensuring alignment with best practices and industry standards.

- Recruit, hire, and onboard top talent, including data scientists and machine learning engineers, to strengthen the team.

- Offer mentorship and guidance, helping team members develop their technical skills and advance their careers.

- Foster a positive, inclusive, and innovative team culture that promotes collaboration and knowledge-sharing.

- Conduct regular performance reviews, set clear objectives, and provide constructive feedback to drive continuous improvement.

DELIVERY LEADERSHIP:

- Oversee and manage complex ML projects from initial concept to successful deployment.

- Ensure the delivery of high-quality outputs on time and within budget, maintaining rigorous standards throughout the project lifecycle.

- Collaborate with Delivery Managers to define project scope, timelines, resource allocation, and...

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