Solutions Architect - (Machine Learning)

Overview

Design, deploy, and scale machine learning systems that power modern data platforms.

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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

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