AI Solutions Engineer (AI/ML)

TL;DR

AI Solutions Engineer (AI/ML): Building and optimizing AI systems for customers, providing technical advice and driving business value with an accent on advising on GenAI and ML best practices. Focus on demonstrating product value, driving product roadmap improvements, and solving complex technical challenges in production ML deployments.

Location: Remote in EMEA

Salary: $125,000–$175,000 annually

Company

hirify.global is a Series C company with over $135M in funding, providing a leading AI & Agent Engineering observability and evaluation platform for enterprises and Fortune 500 companies.

What you will do

• Act as a trusted advisor to sophisticated ML/GenAI teams, building relationships with technical and business stakeholders.
• Advise on GenAI and ML best practices.
• Give ML and LLM product demos to technical and business stakeholders.
• Run strategic business reviews for customers in partnership with the sales team.
• Partner with product and engineering teams to help drive the product roadmap.
• Spearhead new opportunities within existing accounts to help drive expansions.

Requirements

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
• Comfortable working in public Cloud environments (AWS, Azure, GCP).
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn.
• Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy.
• Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations.
• Understanding of GenAI concepts and application evaluation + development lifecycle.
• Proficiency in a programming language (Python, JS/TS, Java, Go, etc).
• Strong Communication Skills - Ability to simplify complex, technical concepts.
• A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Nice to have

• Previous engineering experience in Data Science, MLOps, ML Frameworks, or LLM / Agentic frameworks.
• Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles.
• Prior experience working with applications deployed with Kubernetes.
• Prior experience demoing technical products to both business and technical audiences.

Culture & Benefits

• Remote-first company with optional offices in New York City and the San Francisco Bay Area.
• WFH monthly stipend to pay for co-working spaces.
• Competitive equity package and comprehensive benefits, including medical, dental, vision, and 401(k) plan.
• Unlimited paid time off and generous parental leave plan.
• Mental and wellness support.
• Commitment to Diversity & Inclusion and advancing the use of responsible AI.