Senior Machine Learning Solutions Architect

🕒 il y a 9 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟠 Senior

💻 Ingénieur Solutions

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phData

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2014

🤖 Intelligence artificielle

☁️ SaaS

🏢 Entreprise

💰 €2 500 000 Seed Round en 2018-03

Artificial Intelligence • SaaS • Enterprise

phData est une entreprise spécialisée dans la fourniture de solutions d'ingénierie de données, d'analytique et de migration vers le cloud. Elle propose des services comprenant des stratégies d'IA et d'apprentissage automatique, d'analytique et de visualisation, ainsi que des opérations élastiques pour aider les entreprises à construire et à mettre en œuvre des produits et applications de données modernes. phData est un partenaire d'élite de Snowflake et fournit des services de conseil de bout en bout pour développer des applications de données modernes et traiter efficacement de vastes ensembles de données. Elle répond aux besoins d'industries telles que la santé, les services financiers et la fabrication en optimisant les plateformes de données et en fournissant des informations exploitables grâce à une technologie de pointe et une expertise avérée.

Description

• 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.

🎯 Exigences

• 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.

🏖️ Avantages

• 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