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phData

Machine Learning Principal Solutions Architect

Reposted 11 Days Ago
Remote
Hiring Remotely in US
Senior level
Remote
Hiring Remotely in US
Senior level
As a Principal Solutions Architect, you will design data solutions, provide thought leadership, and enhance client engagement in machine learning.
The summary above was generated by AI

Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean and dbt to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges. 

 

phData is a remote-first global company with employees based in the United States, Latin America and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.

  • 5x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024)
  • Fivetran, dbt, Atlation, Matillion Partner of the Year
  • #1 Partner in Snowflake Advanced Certifications
  • 600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc)
  • Recognized as an award-winning workplace in US, India and LATAM

Our Principal Solutions Architects play a critical role in driving delivery excellence and ensuring customer success. This role is dually responsible for delivery high-quality AI/ML solutions while also driving account growth and strategic client engagement. We are dedicated to hiring not only brilliant engineers, but prescriptive consultants who embody customer obsession. Your ability to combine technical expertise with strategic insight and relationship-building will be essential to elevating our consulting services and driving success for our clients.

As a Principal Solutions Architect on our Machine Learning Engineering team, you are responsible for:

Technical Leadership and Delivery Excellence:

  • Architect end-to-end AI/ML solutions, ensuring scalability, performance, and alignment with customer requirements and goals
  • Lead a team of machine learning engineers and data scientists to build AI/ML platforms, pipelines, and products that meet customer requirements and expectations
  • Communicate business value and ROI of AI/ML solutions to both technical and non-technical stakeholders
  • Mentor team members on best practices in AI/ML architecture, modeling, and technology.
  • Stay abreast of emerging technologies and methodologies in AI/ML to inform solution design and delivery.

Client Engagement and Account Growth

  • Build relationships with client stakeholders to understand their long-term AI/ML goals and design roadmaps that align with business objectives.
  • Craft persuasive technical approaches and value propositions to drive client AI/ML initiatives forward
  • Identify and drive account expansion opportunities by uncovering unmet client needs and where AI/ML can add value.
  • Lead responses to RFIs and RFPs, crafting persuasive technical approaches and value propositions.

Required Experience:

  • 8+ years as a hands-on Solutions Architect, Data Scientist, or Software Engineer that has designed and implemented complex AI/ML platforms and solutions
  • 3+ years previous Consulting leadership experience leading projects, expanding customer relationships and ensuring delivery lead growth
  • 4-year Bachelor's degree in Computer Science or a related field
  • Experience deploying machine learning models in a production setting
  • Proven track record of account expansion, pre-sales, and proposal development
  • Experience leading cross-functional teams of engineers, data scientists, and architects
  • Deep expertise in AI/ML technologies and platforms (e.g., AWS, GCP, Azure, Databricks, Vertex AI, SageMaker)
  • Expertise in Python, Scala, Java, or another modern programming language
  • The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets
  • Development of APIs and web server applications (e.g. Flask, Django, Spring)
  • Complete software development lifecycle experience, including design, documentation, implementation, testing, and deployment
  • Excellent communication and interpersonal skills, with the ability to navigate complex client relationships

You might also have:

  • Master’s or other advanced degree in data science or a related field
  • Relevant side projects (e.g. contributions to an open source technology stack)
  • Experience working with Data-Science and Machine-Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.
  • Experience with Docker, Kubernetes, or some other containerization technology
  • AWS Sagemaker (or Azure ML) and MLflow experience
  • Experience building enterprise ML models

Why phData? We offer:

  • Remote-First Work Environment
  • Casual, award-winning small-business work environment
  • Collaborative culture that prizes autonomy, creativity, and transparency
  • Competitive comp, excellent benefits, 4 weeks PTO plus 10 Holidays (and other cool perks)
  • Accelerated learning and professional development through advanced training and certifications

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.

Top Skills

AWS
Databricks
Docker
Java
Keras
Kubernetes
Python
Scala
Scikit-Learn
Snowflake
Spark
SQL
TensorFlow

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