Solutions Consultant (Machine Learning)

TL;DR

Solutions Consultant (Machine Learning): Partner with Account Executives to own technical discovery, demonstrations, and narratives for biotech/pharma clients building in-house ML capabilities, positioning hirify.global's AI protein design platform. Focus on handling deep technical questions from ML engineers and research leaders, shaping compelling external ML assets, and feeding field insights into product roadmap decisions.

Location: US East (Remote)

Company

Software platform for AI-guided protein discovery and optimization, used by clients in biopharma, biotech, agri-tech, food-tech, and academia. Distributed team of ~75 people across Zurich and Amsterdam.

What you will do

• Own technical discovery with prospects, understanding their ML workflows and protein engineering goals to position hirify.global effectively
• Build and deliver technical demonstrations tailored to ML-savvy audiences including engineering and research leaders
• Drive conversations with computational and ML teams, answering deep technical questions to build credibility
• Develop presentations, demos, and assets to elevate hirify.global's external ML storytelling
• Provide market insights from customer interactions to influence product and ML team roadmaps
• Partner with and mentor other Solutions Consultants to build team technical depth

Requirements

• Graduate degree (MS or PhD) in machine learning, computational biology, computer science, or related field
• Hands-on ML engineering experience: training models, working with sequence/structure data, full stack from pipelines to deployment
• Familiarity with protein engineering or structural biology problems
• Ability to translate technical concepts into persuasive narratives for diverse audiences
• Comfort in fast-paced, customer-facing role with varied conversations
• Willingness to travel 20–30%, including internationally

Nice to have

• Prior experience in solutions consulting, sales engineering, or customer-facing technical roles
• Exposure to LLMs for biological sequences, diffusion models for structure, or similar
• Experience with scientific software like LIMS, ELN, or biopharma R&D toolchains
• Track record of creating technical assets like demos, benchmarks, or write-ups

Culture & Benefits

• Competitive salary, generous equity, wide range of benefits, and career progression
• Focus on building strong team culture in a distributed environment
• Experienced team with successful product history and multi-year funding runway