AI/ML Manager

Summary role description:

Hiring for an AI/ML Manager (CPG or High-Tech Domain) for a high-end start-up AI Strategy and Consulting company.

Company description:

Our client is a start-up AI Strategy and Consulting company, headquartered in San Fransisco, that accelerate business strategies by seamlessly integrating AI, Data, and Digital technologies. They help businesses reimagine workflows, modernize data and digital infrastructure, and reduce tech, process, and talent debt by delivering tailor-made AI solutions that seamlessly integrate into your organization’s existing infrastructure.

Role details:

• Title / Designation: AI/ML Manager
• Location: Mumbai/Bengaluru
• Work Mode: Work-from-Office

Role & responsibilities:

• Lead and mentor a team of AI/ML consultants, driving the design, development, and implementation of AI copilots that enhance the efficiency and effectiveness of organizations
• Involve in data pre-processing, feature engineering, model training, and optimization of machine learning algorithms.
• Additionally, will work on integrating AI copilots into existing systems, analyze data to provide insights, and collaborate with cross-functional teams to understand and address business requirements.
• Work closely with clients to understand their requirements, tailor solutions to their specific needs, and provide technical guidance and support throughout the project lifecycle.
• Drive continuous improvement initiatives, proactively identifying areas for optimization and innovation to maximize client value.
• Share your expertise and best practices with colleagues, mentoring them & contributing to the growth and development of the organization.

Candidate requirements:

• 4+ years of experience in consulting, project management, or a related role, with a strong focus on the healthcare and/or CPG industries.
• Experience with natural language processing (NLP) and/or computer vision (CV) is a plus.
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture.
• Contributions to open-source projects or publications in relevant conferences/journals.
• Familiarity with DevOps practices for continuous integration and deployment (CI/CD).
• Deep understanding of data analytics, data strategy, and digital transformation methodologies, with hands-on experience in implementing data-driven solutions.
• Familiarity with AI technologies, machine learning algorithms, and natural language processing (NLP) techniques.

Selection process:

• 2 Technical Assessments
• HR Discussion

Place of work