Cultivate a deep understanding of the portfolio of machine learning components we utilize, including AI, Gen AI, and LLMs, along with their respective strengths and weaknesses, to provide solutions to existing and future challenges.
Lead the technical architecture for machine learning components and cross-functional ML teams, ensuring integration with advanced AI technologies.
Define the long-term vision for your team, aligning with the company’s strategic and tactical goals, with a focus on machine learning and AI initiatives.
Translate project goals and product roadmaps into organized technical tasks, collaborating with other EMs to ensure alignment.
Guide the team to improve our AI and ML components, ML Ops, and processes through your knowledge of industry trends and tools, along with your own experiences.
Provide guidance and direction to the ML development team to remove obstacles and keep initiatives on target and moving forward.
Coach and mentor developers in the team through technical design sessions, code reviews, and pair programming, with an emphasis on machine learning and AI practices.
Provide technical guidance and support in resolving critical production issues, particularly those related to machine learning and AI.
Collaborate with business and product stakeholders to successfully deliver new machine learning and AI features and capabilities.
Construct design documents and documentation to aid in maintenance and code reuse, particularly for machine learning and AI systems.
Have one-on-one meetings with your team members.
Conduct performance reviews and set accountability for team members.
Requirements & Skills:
Minimum of 5-7 years in software development, including substantial AI/ML experience.
Several years in a leadership role, managing and mentoring teams of engineers and data scientists.
Proven track record in managing complex projects, including planning, execution, and delivery.
Experience working closely with product managers, data scientists, and other stakeholders.
Deep understanding of machine learning algorithms, frameworks (e.g., TensorFlow, PyTorch), and programming languages (e.g., Python, Java).
Strong knowledge of AI/ML concepts, including advanced technologies like Gen AI, LLMs, and semantic search.
Expertise in data handling, preprocessing, and pipeline development, with proficiency in SQL/NoSQL databases.
Ability to analyze large datasets, identify trends, and evaluate model performance using various metrics.
Strong understanding of security architecture and data privacy regulations, ensuring compliance with industry standards.
Ability to solve complex technical problems and drive innovation with a continuous learning mindset.
Practical experience in the production implementation of high-availability AI/ML systems, ensuring reliability and scalability.
Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical audiences.
Ability to adapt to changing technologies and business requirements, fostering a positive and inclusive team culture.
