Director, ML Solution Engineering
Snorkel is seeking our new Pre-sales Leader to lead and build a highly skilled team of Machine Learning Solution Engineers (MLSEs). In this role, you will lead a team of customer facing machine learning solution engineers working directly with our co-founding team, sales team, product team, and engineering team. You will be responsible for training, upskilling and evolving this incredibly gifted team of ML professionals into a team of highly empathetic and curious ML Pre-sales professionals to work alongside our high caliber sales team.
This team will seek to understand the needs of our customers and the challenges they face as they rapidly shift their ML/AI strategy to one centered around Foundation Models. Deep technical experience along with deep GTM (Pre-sales) experience implementing a value centric sales process (with MEDDPICC) will be required for this role.
The MLSE team led by you will be responsible for:
- Educating our clients on a new data centric approach to AI application development for Foundation Models powered by Snorkel. This data centric approach will require re-framing, objection handling, and conviction in an approach that is very much a paradigm shift for many of the largest enterprise organizations in the world
- Educating on Snorkels unique differentiation & capabilities while building strong technical champions
- Documenting detailed PoV execution plans with success criteria that is aligned with Snorkel differentiated capabilities
- Detailed technical discovery to understand current state, future state, pain points, desired outcomes, metrics, and scope.
- Ensure we align the client to the right CV & NLP use cases ideally suited for the Snorkel platform
- Teasing out relevant pain points & challenges from the client while helping the client understand the implication of the pain is no action is taken or alternative solutions are considered. Ensure all pain points have been investigated thoroughly and have corresponding metrics
- Seek to understand the desired future state ML pipeline with improved automation, scale, and collaboration. Highlight notable metrics & impact areas for improvement
- Understand the current state end to end ML pipeline, workflow, and process
- Create elegant current state & future state design workflows to ensure alignment around the end to end current state process as it exists today and a future state redesigned supported by Snorkel
- Build and lead a team of world-class machine learning solution engineers who serve as our first-line expert educators on Snorkel Flow while also being responsible for a process and value-aligned technical evaluation
- Teach, train, enable and upskill our team of incredibly talented machine learning engineers into a team of high caliber technical sellers aligned with our value centric sales playbook & process
- Support a team focused on execution of all stages of the sales process (discovery, current state/future state process mapping, business case quantification, PoV setup & execution)
- Refresh and redesign entire demo catalog. Establish roadmap and timeline for new demo assets
- Act as a trusted advisor on AI; enable customers to solve complex data science problems using Snorkel Flow – including problem framing, data preparation, scripting, model building, model deployment, model management, and output consumption
- Help connect a customer's specific business problems and pain points to Snorkel’s highly differentiated programmatic approach to labeling data and ML application development while quantifying the business value.
- Act as a player/coach working with your team to develop and deliver compelling presentations to customers and prospects
- Enable a team of field experts on the Snorkel Flow platform
- Coordinate cross-functional, dotted-line resources to achieve your team’s goals while maintaining a close working relationship with our co-founders, product, engineering, sales, and marketing teams
- Provide guidance to revenue leaders on sales strategy and product obstacles/gaps, and represent the team's needs to executive staff
- Interpret complex problems, create simple solutions, and collaborate closely with prospects, channel partners, and our sales team to deliver winning solutions
- Innovate and implement strategies that will uplevel your team’s skills
- 7+ years of industry experience in a pre-sales or consulting capacity with 2+ years of direct line management experience (hiring, training, and retaining top talent)
- Industry expertise within machine learning, business intelligence, data analytics. Expertise in cloud computing, and/or SaaS is also important
- Experience building, and evolving pre-sales playbooks based on Force Management Command of the Message (CoM) Value Selling Framework.
- Experience training, teaching non customer facing engineers how to execute a pre-sales value selling process using CoM
- Fluency with scripting in Python and common ML libraries
- Experience with all stages of production ML pipelines, from problem framing and data preparation to model deployment and monitoring (bonus)
- Hands-on experience building and implementing machine learning models (bonus)
- Experience collaborating with business stakeholders to ensure that machine learning solutions deliver successfully on business outcomes
- Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using slides and demos
- Ability to connect a customer's specific business problems and pain points to differentiated product capabilities resulting in clear tangible business benefits or outcomes
- University degree in computer science, engineering, applied mathematics, or a related field, or equivalent experience