Machine Learning Solutions Architect
phData
Machine Learning Solutions Architect
phData
Managed data engineering and ML solutions
Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.
We're growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.
Why phData?
We are looking for a Machine Learning Solutions Architect to join our Applied AI practice team. In this role, you will design and lead practical, production-ready Applied AI solutions that connect data, cloud, and AI technologies to deliver measurable business impact. You will collaborate closely with client stakeholders, senior architects, and cross-functional engineering teams to shape architectures, guide implementation, and move AI initiatives from experimentation into reliable production systems. You will help ensure that phData’s Applied AI solutions are robust, secure, governed, and aligned to each client’s strategic objectives.
Key Responsibilities
Lead the design of end-to-end Applied AI architectures across predictive ML, MLOps, generative AI, RAG, and agentic workflows that are aligned to client goals, constraints, and success criteria.
Translate ambiguous business problems into clear use cases, technical requirements, solution options, and implementation plans that connect AI capabilities to measurable outcomes.
Guide and support delivery teams through discovery, prototyping, implementation, deployment, and productionization, ensuring solutions meet standards for reliability, scalability, security, and governance.
Partner with client stakeholders, senior architects, and sales teams to run discovery and architecture workshops, shape roadmaps, and contribute to proposals, statements of work, and technical demonstrations.
Contribute to practice assets by documenting architecture decisions, patterns, reference designs, and lessons learned that can be reused across clients to accelerate high-quality Applied AI delivery.
About You
You are a technically rigorous, client-focused architect who enjoys solving complex, ambiguous problems in an outcomes-driven environment. You are comfortable operating in distributed, global teams and partnering with colleagues across time zones.
Required Qualifications
Experience
Technical / Functional Skills
Strong understanding of Applied AI and modern ML systems, including predictive ML, MLOps, generative AI, LLM applications, RAG, semantic retrieval, and agentic architectures.
Proven experience architecting and operationalizing production AI/ML systems, including model deployment, inference, monitoring, evaluation, retraining, and governance.
Hands-on experience with modern cloud, data, and AI ecosystems such as Snowflake, Databricks, at least one major cloud provider (AWS, Azure, or Google Cloud), and tools like dbt plus modern AI platforms (for example, Anthropic or OpenAI).
Proficiency in Python and strong working knowledge of SQL for building, integrating, and troubleshooting data- and AI-intensive solutions.
Ability to evaluate technology choices and tradeoffs, integrate AI solutions with enterprise data platforms and applications, and apply CI/CD and productionization practices for AI/ML systems.
Education - If desired
Bachelor's degree in relevant field, or equivalent practical experience.
Preferred Qualifications
Preferred qualifications help candidates stand out but are not required for success in this role.
Experience with advanced agentic AI systems, including orchestration, tool use, planning, memory, multi-agent patterns, or protocols such as MCP.
Experience designing and deploying enterprise-scale RAG systems, semantic retrieval solutions, intelligent workflow automation, and cloud-native AI/ML services (for example, AWS Bedrock or SageMaker, Azure AI/ML, Google Vertex AI, or Snowflake Cortex).
Experience with advanced MLOps capabilities such as model registries, feature stores, data and model lineage, drift detection, AI evaluations, prompt management, or AI gateways.
Experience building reusable accelerators, modular architectures, or multi-client solutions, including contributions to reference architectures, frameworks, or playbooks.
Industry experience applying AI or ML in domains such as life sciences, retail, financial services, manufacturing, or similar enterprise environments, and contributions to technical communities, open-source projects, or thought leadership.
Why phData?
Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.
Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.
Benefits at phData
LATAM:
phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.
phData provides data engineering, data strategy, and machine learning solutions through end-to-end managed services and consulting for enterprises. It delivers cloud data engineering, data migrations, business intelligence, and ML applications by combining data infrastructure automation with analytics and AI strategy in project-based engagements and ongoing support. It differentiates itself by offering full, service-led delivery focused on sustainable data engineering practices and strong customer success, plus its status as an AWS consulting partner with specialized cloud analytics and ML expertise on AWS. Its goal is to help clients turn data into actionable insights and sustainable growth by building scalable data platforms and AI systems guided by clear roadmaps.
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