Sr. Machine Learning Solutions Architect
phDataAbout the role
Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean, and dbt to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges.
phData is a remote-first global company with employees based in the United States, Latin America, and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership, and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.
- 6x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024, 2025)
- Fivetran, dbt, Atlation, and AWS Partner of the Year
- #1 Partner in Snowflake Advanced Certifications
- 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc)
Recognized as an award-winning workplace in the US, India, and LATAM
We are looking for a Sr. Machine Learning Architect to join our Machine Learning team. In this role, you will lead the architecture and implementation of production-grade machine learning and data solutions that enable customers to realize tangible business value from their data. You will collaborate closely with clients, data scientists, data engineers, platform/DevOps teams, and practice leadership to deliver high-quality solutions and advance phData’s delivery excellence.
Key Responsibilities
Client Delivery
- Own and drive end-to-end architecture, solution design, and delivery of machine learning and data solutions for enterprise clients across diverse industries.
- Translate business and data science requirements into scalable technical and MLOps solutions that align with phData methodologies, standards, and best practices.
- Ensure engagements are delivered on time, within scope, and with measurable business value for clients.
- Design and create secure, scalable environments and tooling for data scientists to build, train, and manipulate models and data.
- Work within customer technology ecosystems to extract data from a variety of source systems and place it within analytical and model-training environments.
- Define deployment approaches and production infrastructure for machine learning models, ensuring that businesses can reliably use, monitor, and maintain the models we develop.
- Demonstrate and reveal the business value of data by partnering with data scientists to manipulate and transform data into actionable insights and deployable machine learning models.
- Create and execute operational testing strategies, including QA validation, performance testing, and implementation plans, to support model testing and deployment.
- Ensure the quality, reliability, and observability of delivered solutions through testing, documentation, logging, and monitoring.
Collaboration & Leadership
- Collaborate with cross-functional partners, including data science, data engineering, platform/DevOps, and business stakeholders, to deliver successful client engagements.
- Provide technical and strategic leadership during workshops, discovery sessions, architecture and design reviews, and project delivery.
- Ensure high quality in deliverables through code reviews, documentation, testing, governance, and adherence to security and compliance standards.
- Partner with practice and account leaders to identify opportunities to expand engagements, improve delivery, and standardize patterns for deploying and operating ML solutions.
- Serve as a technical thought leader for clients, recommending technologies and solution designs for model inference,
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