Lead Machine Learning Engineer (Team Lead)

Datatonic

1d•Remote

About The Position

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. 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.

Requirements

Demonstrated leadership and management experience of technical employees.
5+ years of experience in machine learning and data science, with a strong track record of delivering successful projects.
Strong problem-solving and analytical skills.
Proven experience leading and mentoring teams of data scientists and machine learning engineers.
Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences.
Strong software engineering skills with a focus on machine learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn), and cloud platforms, especially Google Cloud Platform (GCP).
Passion for data and a desire to solve real-world problems using machine learning.

Responsibilities

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.
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 key milestones.
Proactively track project progress, identify potential risks, and implement effective mitigation strategies to keep projects on track.
Build and maintain strong, trusted relationships with clients, gaining a deep understanding of their business objectives and challenges.
Communicate complex technical concepts clearly and effectively to both technical and non-technical client stakeholders.
Present project findings, insights, and actionable recommendations in a compelling and client-friendly manner, ensuring alignment with their goals.
Actively participate in the sales process as a subject matter expert, designing robust, scalable ML solutions, scoping Statements of Work (SOW), and providing accurate delivery effort estimates.
Collaborate with fellow technical leads and subject matter experts to architect innovative solutions tailored to client needs.
Lead or contribute to internal initiatives and special projects aimed at advancing the ML practice, including developing new methodologies, enhancing tools, and refining best practices.
Stay current with the latest developments in machine learning and AI, sharing new knowledge and insights with the team to maintain a cutting-edge approach.