phData
Machine Learning Principal Solutions Architect
US-Remote · Principal
Sponsorship not specifiedDetected 147 days ago
PythonJavaScalaDjangoFlaskCode ReviewSQLMySQLSnowflakeRedshiftDatabricksAWSGCPAzureDockerLinuxDevOpsKafkaMachine LearningTensorFlowscikit-learnSparkdbtData Engineering
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Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India.
- We're growing fast, and we give our people real ownership over their work.
- You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams.
Responsibilities
- Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, from model inference, retraining, and monitoring through to production operations.
- Design and create environments for data scientists to build, train, test, and tune AI/ML models and applications using relevant client data.
- Work within customer systems to extract data from a variety of sources and place it within analytical environments to support model development, training, and tuning.
- Define deployment approaches and production infrastructure for AI/ML models and applications, ensuring that businesses can reliably consume and maintain the solutions we deliver.
- Create and execute operational testing strategies, including QA validation, performance testing, and implementation plans to support testing and deployment of AI/ML solutions.
- Collaborate with cross-functional partners including data scientists, ML engineers, data engineers, 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.
- Partner closely with Sales and account leadership to drive account expansion, identify new opportunities, and ensure long-term client value on strategic accounts.
- Lead multiple work streams concurrently, ensuring alignment across technical teams, business stakeholders, and account leadership.
- You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement.
Requirements
- Hands-on experience with big data and analytics ecosystem technologies such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar platforms.
- Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP.
- Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera).
- Proven Account Growth / Revenue Generation experience for external clients
- Experience delivering projects for external or internal clients in a professional services, product, or consulting environment.
- Strong written and verbal communication skills in English, with the ability to present technical concepts to both technical and non-technical audiences.
- Demonstrated ability to work effectively with distributed and cross-functional teams, including Sales, data scientists, ML engineers, data engineers, and business stakeholders.
- Proven track record of taking ownership of client outcomes, managing multiple priorities and work streams, and delivering high-quality work with minimal supervision.
Nice to have
- A Master's or other advanced degree in data science, computer science, or a related field.
- Hands-on experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Experience with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow, and with building enterprise-scale ML models.
- Prior experience in a consulting role or working closely with clients on strategic data and AI/ML initiatives.
- Relevant side projects such as contributions to open source technology stacks, technical communities, speaking, or writing.
- This role is based in the United States and operates primarily in the Central Time Zone.
- Some flexibility may be required to collaborate
Benefits
- Demonstrate the business value of data by partnering with data scientists to manipulate and transform data into actionable insights and deployable machine learning models.
- Take full ownership of client success within AI/ML projects, including planning and vision-crafting, managing client expectations, and handling escalations in a proactive and outcome-oriented manner.
This listing is sourced directly from phData's careers page and normalized into a canonical job model.