Machine Learning Engineer

About Us

We’re on a mission to make manufacturing more resilient.

Basetwo provides manufacturing engineers with a no code AI platform that helps them troubleshoot and optimize their production processes to increase efficiency and reduce waste. Without writing a single line of code, manufacturing engineers can use the Basetwo platform to:

• improve their understanding of their plant
• make better decisions in real-time
• build robust data transformation pipelines
• ingest and connect siloed databases

The Role

Physics-informed Machine Learning is at the heart of the Basetwo platform, and the founding team is looking to bring on a world-class expert in Machine Learning who will be able to make significant technical contributions from data pipelines all the way up to the intelligence layer.

The Machine Learning Engineer will be responsible for deploying and scaling cutting-edge physics-informed machine learning models. Our ideal candidate will partner with Software Engineers, Product Managers and Data Scientists to scale ML solutions on the cloud.

Requirements

What You'll Do

As a Machine Learning Engineer, you will be responsible for:

• Deploying and monitoring large-scale machine learning solutions in production environments for training and inference
• Productionizing research-grade ML code with a focus on simulation, regression, time series forecasting and optimization.
• Developing MLOps infrastructure for model governance, serving, monitoring and retraining.
• Collaborating with cross-functional teams to support product roadmaps for Machine Learning driven solutions

• Setting up and promoting rigorous processes for code review, data quality assessment and engineering reviews.

What You'll Need

To be successful in this role you will have:

• BS or MS in Computer Science or equivalent
• 3+ years of experience in Machine Learning roles
• Strong software engineering skills, troubleshooting and integration skills.
• DevOps/MLOps experience, working experience with Kubernetes, docker, microservices, containerization and deploying software in the cloud.
• Experience with data modelling, data streaming, data transformation, modern data stores
• Experience with Python data stack: dataframes (pandas), statistics (statsmodels), database languages (SQL), data visualization tools (e.g., matplotlib), ML tools (sk-learn, pytorch, etc.), and scientific computing (i.e. scipy)
• You have a disciplined approach to writing unit and integration tests.

• Experience working with major cloud technologies (AWS, Azure, and GCP)

Benefits

• Extended Healthcare Plan (Medical, Disability, Dental & Vision)
• Work From Home - Flexible hours
• Stock Option Plan
• Group Life - AD&D - Critical Illness Insurance
• Paid Time Off Benefits