Senior Manager, DataRobot

• The ideal candidate has a deep understanding of machine learning engineering, cloud platforms, and data pipelines, coupled with strong technical leadership experience
• Hands-on experience in building ML pipelines, deploying models to production, and optimizing ML systems
• Proficiency in programming languages such as Python and familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-Learn
• Strong understanding of data engineering, MLOps, API development, and cloud-based ML environments (AWS, Google Cloud, Azure)
• Proven experience leading and mentoring a team of ML or software engineers
• Track record of delivering complex ML solutions on time with effective team management
• Excellent communication skills, with the ability to explain ML concepts to non-technical stakeholders
• Demonstrated experience building cross-functional relationships and fostering consensus
• Bachelor’s or Master’s degree in Computer Science, Engineering, Machine Learning, or a related field
• 7+ years of experience in machine learning engineering, software engineering
• 3+ years of experience in a technical leadership or management role

Desirable

• As a Senior Manager of Machine Learning Engineering, you will lead teams focused on building and optimizing machine learning systems and data pipelines that power our AI products
• This role is responsible for shaping the strategic and technical direction of the machine learning engineering team, ensuring the development of scalable and reliable ML models and systems
• You will be hands-on in building a robust infrastructure that supports model training, deployment, and monitoring at scale
• As a thought leader, you will collaborate with cross-functional teams to develop innovative, data-driven solutions and seamlessly switch between strategic planning and tactical execution
• Lead, mentor, and manage a team of machine learning engineers specializing in model development, deployment, and optimization
• Foster a collaborative and innovative team environment, upholding our Engineering Operating Principles
• Drive team performance, professional development, and skills advancement
• Conduct regular performance reviews, set goals, and provide constructive feedback
• Provide technical direction on ML system architecture, model deployment pipelines, and scaling solutions
• Oversee the design and implementation of machine learning solutions that meet requirements for scalability, performance, and reliability
• Collaborate with cross-functional partners, including product and design, to prioritize and plan the machine learning team’s work
• Lead the team’s project execution, ensuring alignment with business goals and timely delivery
• Ensure quality of deliverables, upholding standards for code quality, model performance, and system reliability
• Own and maintain the ML services and platforms managed by the team
• Accountable for system availability, setting up monitoring and alerting for key model metrics, and ensuring robust runbooks are in place
• Act as the subject matter expert on machine learning infrastructure, helping address tactical issues as they arise
• Work closely with product managers, data scientists, and other stakeholders to understand requirements and deliver ML solutions that meet business needs
• Continuously seek opportunities to improve ML system performance, reduce model training time, and increase deployment efficiency
• Stay updated with the latest trends and technologies in machine learning engineering, MLOps, and data science tools