{"id":2422970,"url":"https://alion.io/job/phdata-principal-machine-learning-solutions-architect","title":"Principal Machine Learning Solutions Architect","company":{"id":11321,"name":"phData","domain":"phdata.io","url":"https://alion.io/company/phdata","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Solutions","role_family":"Solutions","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":128000,"max_usd":239000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":186},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Anthropic","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Fivetran","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"MySQL","optional":false},{"name":"Oracle","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"H2O.ai","optional":true},{"name":"Keras","optional":true},{"name":"Kubernetes","optional":true},{"name":"MLFlow","optional":true},{"name":"Scikit-learn","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-08-05T15:49:50Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-16T12:12:46Z","board_verified":true,"closed_at":null,"days_open":71,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":71},"description":"JoinphData, 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.\nWe're growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.\nWhy phData?\nSnowflake Implementation Partner of the Year - 7 consecutive years, and 2026 Snowflake AI Partner of the Year\nAWS Premier Tier Services Partner - the highest tier of recognition in the AWS Partner Network\n 2025 Fivetran Partner of the Year (4th consecutive year)\n 2025 dbt Labs Partner of the Year (3x winner) with Visionary partner status\n2026 KNIME Customer Excellence Partner of the Year\n Preferred Partner in the Anthropic Claude Partner Network\n#1 Partner in Snowflake Advanced Certifications\n600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, and more)\nRecognized as an award-winning workplace in the US, India and LATAM\nWe are looking for a Principal Machine Learning Solutions Architect to join our Applied AI team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization, ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, data engineers, platform/DevOps teams, and business stakeholders to deliver high-quality solutions and advance phData's delivery excellence.\nKey Responsibilities:\nOwn 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.\n\nTranslate 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.\n\nLead 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.\n\nEnsure the quality, reliability, and observability of AI/ML solutions through robust testing strategies, documentation, monitoring, and governance that meet security, compliance, and performance expectations.\n\nContribute 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.\n\nAbout You:\nYou 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.\nRequired Qualifications:\n10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.\nTechnical / Functional Skills\nStrong 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.\n\nAbility 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.\n\nHands-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.\n\nFamiliarity 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.\n\nSystems-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.\n\nEnd-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.\n\nWillingness to travel up to 40%, varies based on client needs.\nEducation:\nBachelor’s degree in a relevant technical field (such as Computer Science) or equivalent practical experience.\nPreferred Qualifications:\nPreferred qualifications help candidates stand out but are not required for success in this role.\nExperience 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.\n\nExperience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.\n\nExperience 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.\n\nBackground in consulting or professional services, including pre-sales, project scoping, and strategic advisory work for data and AI/ML initiatives.\n\nContributions to technical communities, open source projects, public speaking, writing, or other relevant side projects demonstrating thought leadership in data and AI/ML.\n\nWhy phData?\nImpactful Work: Partner with leading organizations on meaningful data & AI initiatives.\nCollaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.\nGrowth Opportunities: Access to challenging projects, mentorship, and structured development pathways.\nValues-Driven: We prioritize doing the right thing for our clients, our teams, and our community.\nBenefits at phData\nUS:\nRemote-First Work Environment\n401k plan with company match\nDental and Vision insurance\nHome Office Equipment Stipend\nAnnual stipend for Learning and Development\nCompetitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)\nphData 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. 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