Customer Success Engineer

Responsibilities:

• Serve as the primary internal and external point of contact for your portfolio of existing customers
• Drive adoption and expansions in collaboration with sales by making use cases wildly successful and seeking out additional opportunities
• Lead the new customer onboarding program and work with core Gretel.ai technical teams to ensure that customer requests and critical issues are resolved in a timely fashion
• Maintain a regular communication cadence with your customers, including quarterly/executive business reviews
• Develop a comprehensive understanding of customer health and status through regular customer dialogue and by supervising health and adoption metrics
• Be a customer advocate as we establish our roadmap and influence features and improvements and actively support them through the product development pipeline via collaboration with the product team
• Identify and mitigate the risk of churn with a well-thought-out account add-on strategy built in collaboration with the Account Team
• Become a domain expert on all things ML/Ai and specifically Gretel.ai
• Assist with the development and implementation of standard methodologies, processes, and tools to continually improve our Customer Success Program
• Help author and contribute to market-facing publications, documentation, and FAQs
• Continuously educate your existing customers and additional business units through lunch and learns, educational workshops etc.
• Build and own the strategy to make the initial use cases successful and find new use cases within the organization to expand Gretel’s footprint

Requirements:

• 3+ years of demonstrated ability working in a technical customer-facing role, e.g., technical account management, management consultant, pre-sales engineer or customer success.
• Consistent record of achieving targets and goals with a history of driving adoption and identifying risks to renewals, cross-selling, and upselling.
  
• Working knowledge of ML Ops and methodologies
  
• Experience using one or more of the following packages: TensorFlow/Keras, PyTorch Lightning, HuggingFace 
  
• Experience setting up code/data pipelines, automation, databases, and/or containerized workloads on cloud platforms (AWS, GCP, Azure) 
  
• Proficiency in Python, Data Analysis tools such as Pandas, Scikit-Learn, Plotly
  
• World-class reliability – our customers will expect rapid responses to product questions
  
• Willing to go the extra mile, great work ethic, resourceful, “get it done” attitude