AI Engineering Manager

As an AI Engineering Manager, you will play a crucial role in guiding a team of talented engineers to build innovative and high-performance AI solutions. Your responsibilities will include: - **Team Leadership & Development**: - Lead, mentor, and inspire a team of AI/ML engineers and data scientists. - Conduct regular one-on-ones, performance reviews, and provide continuous feedback to support professional growth. - **Technical Strategy & Vision**: - Develop and execute the technical strategy for AI initiatives, aligning it with company-wide goals. - Define the technology stack, architectural patterns, and best practices for model development, deployment, and monitoring. - **Project & Budget Management**: - Oversee the entire project lifecycle for AI projects, from ideation to production. - Ensure projects adhere to timelines and budgets, and are delivered with high quality. - **Performance Monitoring**: - Define and implement key performance indicators (KPIs) for the engineering team and AI models. - Regularly report on performance to stakeholders. - **Stakeholder Communication**: - Act as the primary point of contact for the engineering team. - Effectively communicate project status, goals, and technical challenges to both technical and non-technical stakeholders. - **Cross-Functional Collaboration**: - Coordinate with product managers, data scientists, and other internal teams to ensure seamless project execution and alignment on goals. **Qualifications**: - **Education**: - Bachelor's degree in Computer Science, Engineering, or a related field. A Master's or Ph.D. with a specialization in Machine Learning or Artificial Intelligence is a significant plus. - **Experience**: - 3+ years of experience in a management or lead role within an engineering team. - Proven hands-on experience in the AI/ML domain, including developing and deploying machine learning models, working with large datasets, and managing data pipelines. - Experience with cloud platforms (e.g., AWS, GCP, Azure) and their AI/ML services (e.g., Sagemaker, Vertex AI, MLFlow). **Technical Skills (AI Focus)**: - Strong understanding of core machine learning concepts. - Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Proficiency in programming languages commonly used in AI/ML, such as Python and R. - Experience with data processing and big data technologies like Spark, Hadoop, or Dask. - Knowledge of MLOps principles and tools for model versioning, serving, and monitoring. You should possess exceptional interpersonal and communication skills, strong leadership and mentoring abilities, excellent problem-solving skills, and the ability to thrive in a dynamic, fast-paced environment while managing multiple priorities effectively.,