Remote ML Solutions Architect – Enterprise AI & Data

Jobot; Chicago (IL); On-site; USD 160,000 - 210,000; Full time

Job summary

Jobot is seeking a Solutions Architect on our Machine Learning Engineering team to design and implement data solutions spanning the entire ML lifecycle, including model inference, retraining, monitoring, and beyond. You will guide technology choices from the application layer to the infrastructure layer, leveraging your Python, Java, and Scala skills to build and operate production environments.

You will create environments for data scientists, analyze customer tech stacks, and define deployment

Qualifications

• Bachelor’s degree in Computer Science or related field.
• 6+ years of experience in ML/Software/Data engineering roles.
• Experience deploying ML models into live production environments.
• Proficiency in Python, Scala, Java or similar languages.
• Ability to build robust data pipelines and optimize SQL queries.
• Hands-on with Spark, Snowflake, Databricks and related tech.

Responsibilities

• Design and implement data solutions across the ML lifecycle from inference to monitoring.
• Provide thought leadership on technologies and designs across application and infrastructure layers.
• Lead environments for data scientists and build production-grade environments.
• Analyze customer environments and securely integrate data into analytics platforms.
• Define deployment approaches and scalable infrastructure for models.
• Partner with data scientists to transform raw data into actionable insights.
• Ensure lifecycle maintainability, security, and performance of delivered solutions.

Skills

Python

Scala

Java

Machine Learning

Data Pipelines

SQL

Spark

Snowflake

Databricks

Kafka

APIs

Education

Bachelor’s degree in Computer Science

Tools

Flask

Django

Spring

Kafka

Spark

Snowflake

Databricks

Job description

Jobot is seeking a Solutions Architect on our Machine Learning Engineering team to design and implement data solutions spanning the entire ML lifecycle, including model inference, retraining, monitoring, and beyond. You will guide technology choices from the application layer to the infrastructure layer, leveraging your Python, Java, and Scala skills to build and operate production environments.

You will create environments for data scientists, analyze customer tech stacks, and define deployment