Senior Machine Learning Solutions Architect
Posted 13hrs ago
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Job Description
Senior Machine Learning Architect at phData collaborating with clients on data-driven AI solutions. Leading architecture and implementation for machine learning and data projects.
Responsibilities:
- 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.
- 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, retraining, monitoring, and lifecycle management from the application layer down to infrastructure.
- Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, playbooks, and training related to machine learning engineering and MLOps.
- Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.
- Act as a trusted advisor to senior client stakeholders, shaping roadmaps, influencing strategic decisions, and guiding long-term initiatives.
- Mentor and coach team members, fostering a culture of learning, feedback, and continuous improvement.
- Help define and refine practice standards, reusable assets, and delivery frameworks.
Requirements:
- 6+ years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer building and deploying production data and machine learning solutions.
- Hands-on expertise in modern programming languages such as Python, Scala, Java, or similar, including experience developing APIs and web applications using frameworks such as Flask, Django, or Spring.
- Experience building and operating robust data pipelines and distributed data processing solutions using SQL and big data technologies (e.g., Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS).
- Strong systems-level knowledge of network and cloud architecture, Linux-based operating systems, and data/storage platforms (e.g., AWS, Databricks, Cloudera), with familiarity across data and messaging systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP; proven experience deploying machine learning models in production environments.
- Strong working knowledge of SQL and the ability to write, debug, and optimize complex and distributed queries.
- Hands-on experience with one or more big data ecosystem products and languages such as Spark, Snowflake, Databricks, etc.
- Production experience in core data technologies and platforms (e.g., Spark, HDFS, Snowflake, Databricks, Redshift, Amazon EMR).
- Complete software development lifecycle experience, including design, documentation, implementation, testing, deployment, and ongoing operations.
- Excellent communication and presentation skills, with previous experience working directly with internal or external customers.
- Participating in pre-sales or project scoping; as well as account growth / revenue generation with external clients
- Experience delivering projects for external or internal clients in a professional services or consulting environment.
- Ability to break down complex problems into structured, actionable steps and drive them through to completion.
- Strong written and verbal communication skills in English.
- Demonstrated ability to work effectively with distributed and cross-functional teams, including data scientists, engineers, and business stakeholders.
- Proven track record of taking ownership, managing multiple priorities, and delivering high-quality work with minimal supervision.
- Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience preferred.
Benefits:
- Remote-First Work Environment
- Casual, award-winning small-business work environment
- Collaborative culture that prizes autonomy, creativity, and transparency
- Competitive comp, excellent benefits, generous PTO plan plus 10 Holidays (and other cool perks)
- Accelerated learning and professional development through advanced training and certifications


















