Key Responsibilities
Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, ensuring reliable model deployment, retraining, monitoring, and production operations that create clear business impact.
Translate complex business and data science requirements into scalable, secure, and resilient AI/ML architectures, defining the environments, data flows, and infrastructure required for model development, training, tuning, and serving.
Lead technical and strategic client engagements, including workshops, discovery sessions, and architecture reviews, to align stakeholders on AI/ML roadmaps, deployment approaches, and production-readiness standards.
Ensure the quality, reliability, and observability of AI/ML solutions through robust testing strategies, documentation, monitoring, and governance that meet security, compliance, and performance expectations.
Contribute to and leverage reusable assets such as reference architectures, accelerators, templates, and playbooks, while mentoring team members and partnering with Sales and account leadership to grow strategic AI/ML engagements.
About You
You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. 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. You are comfortable operating in distributed, global teams and partnering with colleagues across time zones.
Required Qualifications
10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.
Technical / Functional Skills
Strong proficiency in a modern programming language such as Python (or similar) for building production-grade data and ML solutions, including experience designing and integrating APIs and services that expose ML models.
Ability to build and operate robust data pipelines across diverse data sources and toolsets, with strong working knowledge of SQL and experience writing, debugging, and optimizing complex and distributed queries.
Hands-on experience with big data and analytics platforms such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar large-scale data processing and storage technologies.
Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP, and how they integrate into analytical and ML environments.
Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera), with proven experience designing and operating production ML systems for performance, security, scalability, and reliability.
End-to-end software development lifecycle experience (design, documentation, implementation, testing, deployment, and ongoing operations) for data and ML solutions, including model deployment, monitoring, and lifecycle management.
Willingness to travel up to 40%, varies based on client needs.
Education
Bachelor’s degree in a relevant technical field (such as Computer Science) or equivalent practical experience.
Preferred Qualifications
Preferred qualifications help candidates stand out but are not required for success in this role.
Experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP in the context of building and operating AI/ML solutions.
Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.
Experience with containerization and orchestration technologies such as Docker and Kubernetes, and with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow for enterprise-scale ML.
Background in consulting or professional services, including pre-sales, project scoping, and strategic advisory work for data and AI/ML initiatives.
Contributions to technical communities, open source projects, public speaking, writing, or other relevant side projects demonstrating thought leadership in data and AI/ML.
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
US
Remote-First Work Environment
401k plan with company match
Dental and Vision insurance
Home Office Equipment Stipend
Annual stipend for Learning and Development
Competitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)
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.
