AI/ML Consultant

As an AI/ML Consultant, you would be developing AI-powered companions such as Pricing Copilot, Sales Copilot, Customer Experience Copilot, etc. The Sales Copilot for example will provide sales insights, automate routine tasks, and assist sales teams in making informed decisions, ultimately improving the overall sales efficiency. Leveraging your expertise in data analytics, digital transformation, and AI technologies, you will collaborate closely with clients to understand their unique challenges, identify opportunities for improvement, and design tailored solutions that deliver measurable value.

Responsibilities:

AI/ML Consultants will be responsible for designing, developing, and implementing AI-driven business copilots that enhance the efficiency and effectiveness of organizations.
They will be involved in data pre-processing, feature engineering, model training, and optimization of machine learning algorithms.
Additionally, they 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.
AI/ML Consultants will 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 and contributing to the growth and development of the AuxoAI team.

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.