ML Solutions Engineer

As an a ML Solutions Engineer you will:

• Build strong, meaningful relationships with our customers and proactively seek to understand their technical and business objectives
• Drive technical engagement and adoption across the complete customer journey
• Champion customer needs internally, advocating for them within Robust Intelligence and leveraging your customer knowledge to influence the product roadmap
• Coordinate across multiple Robust Intelligence teams, including Product, Engineering, Sales, and Support to advance adoption, expansion, and other Customer Success priorities
• Become a power user of the RI platform: deeply understand the user experience (using the APIs, navigating the GUI, integrating with different platforms, etc.)
• Create and deliver tailored product demonstrations that address technical pain and show business value
• Design high-quality, differentiated proofs of concept that establish the value of the Robust Intelligence platform
• Scope customer engagements; investigate and understand customer needs
• Build bespoke machine learning validation solutions using the RI platform
• Work with customers to architect integrations with their existing machine learning stack
• Work with customers to design best practices, processes, and frameworks for their organization
• Gather, understand, and communicate customer feedback to RI’s Product and Engineering teams
• Own customer-facing technical communications to ensure a professional and concise message

What we look for:

• At least five years of professional experience with machine learning, ML operations, data science, or a related field
• Experience building ML models and putting them into production
• Strong expertise in AI, ML, data science, or related spaces; general knowledge of statistics and applied ML
• Knowledge of Python (or other programming languages)
• Significant knowledge of the artificial intelligence ecosystem; a deep understanding of how data scientists and machine learning engineers develop and deploy AI models
• Experience with tooling and platforms in the ML ecosystem (Huggingface, MLFlow, Databricks, DataRobot, etc.)
• Self-motivated and excited to work at a startup; comfortable with ambiguity, eager to learn, and able to thrive with little to no direct, daily oversight
• Strong communication skills (business fluency in spoken and written English)
• Ability to travel about 25% of the time to meet with your accounts

Preferred qualifications:

• Experience in customer success, sales, sales engineering, consulting, or other customer-facing fields
• Familiarity with customer success and sales processes
• Knowledge of REST, Kubernetes, Docker, and Unix
• Familiarity with major public cloud platforms (e.g. AWS, Google Cloud Platform, Azure) and their ML products (AWS Sagemaker, GCP Vertex AI, etc.)
• Ability to establish trust at the CxO level as well as with technology practitioners
• Experience developing and delivering product demonstrations and leading proofs of concept
• Bachelor’s degree (or equivalent) in computer science, engineering, mathematics, statistics, or another quantitative field