ML Engineer

Product & Engineering Boston, MA United States


Company Overview 

AtScale enables smarter decision-making by accelerating the flow of data-driven insights. The company's semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across all industries. With AtScale customers are empowered to democratize data, implement self-service BI and build a more agile analytics infrastructure for better more impactful decision making.  

Job Description

As an ML Engineer at AtScale, you will not just apply machine learning to standard use cases, but help us build better tools that enable our customers to do so. We're building new tools that innovate on AI workflows. This is an opportunity to help build a new business from the ground up, within an existing market and company. 

  • Partner with product management, business development, and sales engineers teams to define market opportunity and requirements
  • Collaborate to design, document, and implement new solutions that address core challenges of AI workflows
  • Extend existing data science tools and develop new APIs that address key challenges in common data science tasks
  • Work closely with external users and customers (data scientists, machine learning engineers, business analysts) to pilot new offerings
  • Help establish best practices, document designs, and mentor junior team members
  • Manage junior team members as necessary 
  • Define requirements, estimate work, track dependencies, report progress, highlight blockers
  • BA/BS preferred in a technical or engineering field
  • 3+ years combined python engineering and machine learning experience
  • Proficiency developing in Python and associated toolkits (numpy, pandas, scipy)
  • Experience in popular machine learning libraries (Spark, TensorFlow, XGBoost, Sci-kit learn)
  • Strong command of software engineering fundamentals including microservices (e.g. REST/JSON based APIs)
Preference will be given to candidates with
  • Experience working with one of the cloud providers like AWS, MSFT Azure, or GCP
  • Experience with data science and machine learning platforms like DataRobot, Dataiku, Sagemaker, AzureML,, Databricks
  • Strong understanding of data warehouse concepts and working experience with relational databases and cloud data warehouse (Snowflake, Databricks, Redshift, BigQuery, Synapse)
  • Experience with DevOps workflows like Airflow, MLFlow, Tecton and tools like GitHub
Join a team of passionate people committed to redefining the way business intelligence and AI is done.
For additional information, visit