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Solution Architect

Remote: 
Full Remote
Contract: 
Experience: 
Senior (5-10 years)
Work from: 

Scribble Data logo
Scribble Data Startup https://www.scribbledata.io/
11 - 50 Employees
See more Scribble Data offers

Job description

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Your missions

About Scribble Data

Scribble Data is an advanced analytics and LLM data products platform company. 

Our Enrich Intelligence platform is built to help teams rapidly build trustworthy data products for high-impact advanced analytics use cases. Enrich provides a full-stack solution for data preparation and lightweight machine learning (ML) algorithm execution, coupled with a low-code consumption interface designed for business users. With the launch of its new Hasper engine, organizations can now utilize large language models (LLMs) to bridge the gap between decision workflows and natural language, combining machine learning with a built-in rules engine. 

For added security and trust, Enrich offers various secure hosting options for customers, ranging from on-premise to virtual private cloud. 

We work smart, invest in tools and tech that are on the cutting edge of advanced analytics, and package all that we’ve learnt about efficiency and data mileage into our products. To know more, visit www.scribbledata.io.

About the role

Our customers trust us with their data and the outputs, and expect cutting-edge tools and thought processes from us. Product is at the center of the relationship. The Solution Architect role owns this relationship managing the delivery to these customers, guiding their data science teams on best practices, advising them on their data roadmap, helping them build datasets, and simultaneously communicating with their leadership.

The Solution Architect role is hands-on. 
  • You will help potential customers frame their problems into the scope for a PoC, build and own this PoC atop Enrich, convert them into long-term customers, and own the delivery and relationship end-to-end. 
  • You will focus on delivery for each customer, with high attention-to-detail. You will be responsible for ensuring trust, robustness, performance, and ease of use of the platform in each customer’s context, and depending on the size of the individual customer engagement, you may lead a team of engineers as well. 
  • You will manage people and vendors. You might even need to travel, look squarely into the eyes of many customers and sell. You'll often receive feedback and new asks from customers and be able to work that into your delivery.
  • You will track and research emerging trends in the space, as well as moves that our competitors are making, thereby creating nice feedback loops for our product team. 

About Enrich
Enrich is a full-stack solution in Python that enables customers to build internal-facing data products with MLRS (ML at Reasonable Scale) robustly and quickly. It trades scale of data for speed of development and deployment, strong auditability, and lower skill. It is a fully Python stack with single server packaged deployment with support for containerization if required. Simplicity and minimality are major considerations in everything that we do.

Your Strengths
  • Proven record of hands-on data science and/or ML engineering experience
  • 8+ years of industry experience owning, building, and shipping data-driven solutions to production 
  • Fluent in Python and SQL (you have deployed production-grade code and not just developed prototypes in Jupyter notebooks including packaging)
  • Strong algorithmic and data structure skills 
  • Experience developing and implementing best-in-class algorithms for multiple among user modeling, entity matching, recommendation systems, search systems, natural language understanding, and time series analysis
  • Proficient with Python data science libraries (pandas, numpy, scikit-learn, spacy, etc.)
  • Experience with R, Matlab or other statistical computing languages
  • Experience with deep learning frameworks like Tensorflow, Keras, PyTorch, etc.
  • Experience with Langchain or other LLM development frameworks is a plus
  • Comfortable with big data technologies like map-reduce, noSQL, Spark, HBase, Hive
  • Having built and shipped a product at a startup will be a plus
  • Record of published patents along with technical publications in peer-reviewed conferences and journals will be a plus
  • Masters degree or higher in Computer Science with a background in statistics
  • Strong communication and collaboration skills to work with stakeholders from different backgrounds

Does this sound like you?
  • You like adventure and have a stomach for learning and unlearning every day
  • You are excited by powering up a whole generation of upcoming data applications
  • You dream big and believe that hard problems need streamlined systems and massive amounts of data to tackle effectively
  • You embrace uncertainty and can develop processes and systems to handle rapidly evolving requirements
  • You have the discipline to take audacious goals and break down years-long roadmaps into near term deliverables that provide value to business stakeholders
  • You enjoy educating your customers and team members about what it means to be data-oriented and cultivating engineering best practices
  • You are comfortable selling to customers (not a biggie)
  • You have a sense of humor

GET EXCITED. Because you're about to make a huge impact. 

Scribble Data is growing rapidly. We think of this phase of hiring as extending Scribble's core team, so if you want to get in on the ground floor, now would be a good time to look our way.

WHAT WE OFFER
  • Primarily remote work
  • A work culture that helps you innovate and evolve continuously
  • A chance to shape the future of ML, marrying it with generative AI

Interested? 
Send us your resume at hello@scribbledata.io 
 
Know of someone else who you think should see this? Spread the word. Tell that friend who is perfect for this role.

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
Check out the description to know which languages are mandatory.

Soft Skills

  • Open Mindset
  • Collaboration
  • Communication

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