Jobot is hiring: Solutions Architect - (Machine Learning) in Austin
Jobot, Austin, TX, United States
Overview
Design, deploy, and scale machine learning systems that power modern data platforms.
This Jobot Job is hosted by: Robert Donohue. Easy Apply now by clicking the "Easy Apply" button and sending us your resume.
Salary: $150,000 - $190,000 per year
About us
We’re a remote-first, global leader in the modern data stack, partnering with some of the most influential cloud and data platforms in the world to help enterprises solve complex data and machine learning challenges. Our teams work at the intersection of data engineering, analytics, and machine learning—designing and delivering real-world solutions that move beyond experimentation into production.
With team members across the U.S., Latin America, and India, we foster a culture built on technical curiosity, ownership, trust, and collaboration. Even as we scale rapidly, we’ve maintained a flexible, high-energy environment where top talent is empowered to do their best work.
Why join us
Competitive Compensation:
$140,000 – $190,000+ base salary (depending on experience)
Remote-First:
Work from anywhere in the US with occasional customer-site travel nationwide
Massive Growth:
Be part of a company growing 40% YOY, creating career advancement opportunities
Cutting-Edge Tech:
Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more
Award-Winning Culture:
Collaborative, inclusive, and committed to professional development
Learning & Development:
Accelerated training, advanced certifications, and exposure to AI/ML innovation
Time Off & Benefits:
4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks
Job Details
Machine Learning Solutions Architect (Remote – U.S.)
This role sits at the core of turning machine learning ideas into production-ready solutions. You’ll design, build, deploy, and operate scalable ML systems—partnering closely with data scientists, engineers, and client stakeholders to ensure models deliver real business value.
What You’ll Do
Design and implement end-to-end machine learning solutions, including inference, retraining, monitoring, and lifecycle management
Architect and build environments that enable data scientists to develop and deploy models efficiently
Define deployment strategies and infrastructure to ensure models operate reliably in production
Work directly within customer systems to extract, transform, and prepare data for analytics and ML use cases
Partner with data scientists to convert experimental models into scalable, maintainable solutions
Design operational testing strategies and oversee QA, validation, deployment, and ongoing optimization
Provide technical thought leadership across application, data, and infrastructure layers
What We’re Looking For
6+ years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
Hands-on experience deploying ML models into production environments
Strong programming skills in Python, Scala, Java, or similar languages
Experience building and operating robust data pipelines and distributed systems
Solid SQL expertise with experience optimizing complex queries
Familiarity with modern data platforms such as Spark, Snowflake, Databricks, or similar
Working knowledge of cloud platforms (AWS, Azure, or GCP) and production data ecosystems
Experience developing APIs and backend services (e.g., Flask, Django, Spring)
Excellent communication skills and comfort working with both technical and business stakeholders
Nice to Have
Advanced degree in data science or a related field
Experience with ML frameworks (TensorFlow, Keras, scikit-learn, etc.)
Docker and Kubernetes experience
Exposure to AWS SageMaker, Azure ML, MLflow, or enterprise ML platforms
Open-source contributions or relevant side projects
Interested in hearing more? Easy Apply now by clicking the "Easy Apply" button.
Want to learn more about this role and Jobot?
Click our Jobot logo and follow our LinkedIn page!
#J-18808-Ljbffr
Design, deploy, and scale machine learning systems that power modern data platforms.
This Jobot Job is hosted by: Robert Donohue. Easy Apply now by clicking the "Easy Apply" button and sending us your resume.
Salary: $150,000 - $190,000 per year
About us
We’re a remote-first, global leader in the modern data stack, partnering with some of the most influential cloud and data platforms in the world to help enterprises solve complex data and machine learning challenges. Our teams work at the intersection of data engineering, analytics, and machine learning—designing and delivering real-world solutions that move beyond experimentation into production.
With team members across the U.S., Latin America, and India, we foster a culture built on technical curiosity, ownership, trust, and collaboration. Even as we scale rapidly, we’ve maintained a flexible, high-energy environment where top talent is empowered to do their best work.
Why join us
Competitive Compensation:
$140,000 – $190,000+ base salary (depending on experience)
Remote-First:
Work from anywhere in the US with occasional customer-site travel nationwide
Massive Growth:
Be part of a company growing 40% YOY, creating career advancement opportunities
Cutting-Edge Tech:
Build enterprise-scale solutions leveraging Snowflake, Databricks, AWS, GCP, Azure, Kafka, and more
Award-Winning Culture:
Collaborative, inclusive, and committed to professional development
Learning & Development:
Accelerated training, advanced certifications, and exposure to AI/ML innovation
Time Off & Benefits:
4 weeks PTO, 10 paid holidays, health/dental/vision insurance, 401(k), and additional perks
Job Details
Machine Learning Solutions Architect (Remote – U.S.)
This role sits at the core of turning machine learning ideas into production-ready solutions. You’ll design, build, deploy, and operate scalable ML systems—partnering closely with data scientists, engineers, and client stakeholders to ensure models deliver real business value.
What You’ll Do
Design and implement end-to-end machine learning solutions, including inference, retraining, monitoring, and lifecycle management
Architect and build environments that enable data scientists to develop and deploy models efficiently
Define deployment strategies and infrastructure to ensure models operate reliably in production
Work directly within customer systems to extract, transform, and prepare data for analytics and ML use cases
Partner with data scientists to convert experimental models into scalable, maintainable solutions
Design operational testing strategies and oversee QA, validation, deployment, and ongoing optimization
Provide technical thought leadership across application, data, and infrastructure layers
What We’re Looking For
6+ years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
Hands-on experience deploying ML models into production environments
Strong programming skills in Python, Scala, Java, or similar languages
Experience building and operating robust data pipelines and distributed systems
Solid SQL expertise with experience optimizing complex queries
Familiarity with modern data platforms such as Spark, Snowflake, Databricks, or similar
Working knowledge of cloud platforms (AWS, Azure, or GCP) and production data ecosystems
Experience developing APIs and backend services (e.g., Flask, Django, Spring)
Excellent communication skills and comfort working with both technical and business stakeholders
Nice to Have
Advanced degree in data science or a related field
Experience with ML frameworks (TensorFlow, Keras, scikit-learn, etc.)
Docker and Kubernetes experience
Exposure to AWS SageMaker, Azure ML, MLflow, or enterprise ML platforms
Open-source contributions or relevant side projects
Interested in hearing more? Easy Apply now by clicking the "Easy Apply" button.
Want to learn more about this role and Jobot?
Click our Jobot logo and follow our LinkedIn page!
#J-18808-Ljbffr