AI / ML Consultant

Team: Client Services

Location: Remote (US)

Commitment: Contract

Workplace Type: remote

Overview

• Work with technology companies to identify improvements of existing technology, organizations, processes, and tools used to develop software products and services. 
• Work with private equity companies and other investment firms to help them understand the technology strengths, risks, and opportunities for improvement for potential investments (I.e. technical due diligence) 
• Design and implement solutions from scratch (e.g. Agile methodology transformations), guiding and mentoring more junior software developers and other engineers.
• Collaboratively work in partnership with internal and client technical leads and team members.

Expected Results

• Be an apprentice consultant for your first 2 projects and then be willing and able to drive a project on your own to successful completion, including collaboration, project management, and getting your hands dirty
• Participate in and drive AI assessment efforts on behalf of investment companies, collaborating, digging deep, and creating a report for the investors to outline technical investment risks
• Participate in hands-on implementation projects using processes and technologies that are most applicable to you, producing stellar customer feedback along the way
• Work with technology companies to identify improvements of existing AI technology, organizations, processes, and tools.
• Work with private equity companies and other investment firms to help them understand the technology strengths, risks, and opportunities for improvement for potential investments.
• Collaboratively work in partnership with internal and client technical leads and team members

Requirements

• In-depth expert-level experience in Data Science domain (data mining, statistics, machine learning, etc.) and AI domain:
• Analytical and generative AI
• Evaluation of available data assets and their profile
• Current knowledge of LLM landscape, commercial and open course
• Model selection, training, fine-tuning
• Model efficacy metrics, bias management
• IP considerations
• ML Ops and related tooling
• Cloud hosting options and self-hosting, and related economics
• Multi-modal AI (text, NLP / voice, images, video)
• AI-enabled software engineering

Education

• Advanced degree in computer science, statistics, advanced analytics, data science, machine learning, AI