AI ML Consultant - Senior Associate/Manager

Role Summary

As a AI/ML Consultant, you would be developing AI powered companions such as Pricing Copilot, Sales Copilot, Customer Experience Copilot etc. The Sales Copilotfor example will provides sales insights, automateroutine tasks, and assists sales teams in making informed decisions, ultimately improving the overall sales efficiency. Leveraging your expertisein data analytics, digital transformation, and AI technologies, you will collaborate closely with clientsto understand their unique challenges, identify opportunities for improvement, and design tailored solutions that deliver measurable value.

Responsibilities

1. AI/ML Consultants will be responsible to design, develop, and implement AI-driven business copilots that enhance the efficiency and effectiveness of organizations
2. They will be involved in data pre-processing, feature engineering, model training, and optimization of machine learning algorithms
3. 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
4. AI/ML Consultants will work closely with clients to understand their requirements, tailor solutions to their specific needs, and provide technical guidanceand support throughout the project lifecycle
5. Drive continuous improvement initiatives, proactively identifying areas for optimization and innovation to maximize client value.
6. Share your expertise and best practices with colleagues, mentoring them & contributing to the growth and development of the AuxoAI team.

Qualifications

1. 4+ years of experience in consulting, projectmanagement, or a related role, with a strong focuson the healthcare and/or CPG industries.
2. Experience with natural languageprocessing (NLP) and/orcomputer vision (CV) is a plus.
3. Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture.
4. Contributions to open-source projectsor publications in relevant conferences/journals.
5. Familiarity with DevOps practicesfor continuous integration and deployment (CI/CD).
6. Deep understanding of data analytics, data strategy, and digital transformation methodologies, with hands-on experience in implementing data-driven solutions.
7. Familiarity with AI technologies, machine learning algorithms, and natural languageprocessing (NLP) techniques.