Machine Learning Architect

Company: phData
Location: Seattle
Posted on: January 17, 2022

Job Description:

phData works exclusively in the realm of data and machine learning. By partnering with the biggest cloud data platforms (Snowflake, Azure, AWS, Cloudera), we're able to help the world's largest companies solve their toughest challenges.

Our work is challenging and our standards are high, but we invest heavily in our employees, starting with a 4 week bootcamp to ensure you'll be successful. Plus, you'll get to work with the brightest minds in the industry and the latest data platforms on the market. And, because the data and ML industry is changing rapidly, you will always have the opportunity to learn - whether that's a new technology, diving deeper into your preferred stack, or picking up an entirely new skill set.

Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow them the autonomy to deliver results. Our award winning workplace fosters learning, creativity and teamwork.

Best Places to Work (2017, 2018, 2019, 2020, 2021)
Inc. 5000 Fastest Growing US Companies (2019, 2020, 2021)
Snowflake Emerging Partner of the Year 2020
Databricks Rising Star Partner of the Year 2020
Cloudera Partner of the Year 2020

If you're a Machine Learning Architect and enjoy solving complex, enterprise-scale data challenges, you'll love phData. Our talented team of Data Scientists and Machine Learning Engineers serve as key technical leaders to help customers (including best brands in the world) gain tangible value from their data. And best of all, our award-winning culture is ideal for folks who enjoy collaboration, learning and growth in an entrepreneurial environment.

Machine Learning Architects are the Swiss army knives of machine learning. They're ready for anything, and they bring all the tools to ensure that machine learning models see the light of day. They own the infrastructure and deployment plan - from making sure data science models can actually be built using customer data to deploying them into a production environment, and everything in between.

At phData, Machine Learning Architects are responsible for designing and implementing data solutions best-suited to deliver on our customer needs and use cases - from streaming, to data lakes, to analytics, and beyond across a progressively evolving technical stack. They provide thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure; and they have the team leadership and coding skills (e.g. Python, Java, and Scala) to get their solutions into production - and to help ensure performance, security, scalability, and robust data integration.

As a Solutions Architect on our Machine Learning Engineering team you are responsible for:
Designing and implementing data solutions best-suited to deliver on our customer needs and use cases - from model inference, retraining, monitoring, and beyond - across a progressively evolving technical stack.
Providing thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure; and they have the team leadership and coding skills (e.g. Python, Java, and Scala) to get their solutions into production; and to help ensure performance, security, scalability, and robust data integration.

What you'll do in this role:
Design and create environments for data scientists to build models and manipulate data
Work within customer systems to extract data and place it within an analytical environment
Learn and understand customer technology environments and systems
Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop
Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models
Partner with data scientists to ensure solution deployability-at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle
Create operational testing strategies, validate and test the model in QA, and ensure the quality of the delivered product

This job might be for you if you bring...
At least 4 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
4-year Bachelor's degree in Computer Engineering or a related field
Experience deploying machine learning models in a production setting
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
Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries
Hands-on experience in one or more big data ecosystem products/languages such as Spark, Snowflake, Databricks, etc.
Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)
Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), storage systems (e.g., AWS, Databricks, Cloudera)
Production experience in core data technologies (e.g. Spark, HDFS, Snowflake, Databricks, Redshift, & Amazon EMR)
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 presentation skills; previous experience working with internal or external customers

And you're exceptional at...
Thinking independently and seeing the big picture
Translating customer needs into solutions
Confidently standing behind your recommendations
Exploring new technologies in an effort to always grow and uncover better ways to solve problems (for instance: automating all the things)
Explaining your technical decisions, both internally and externally
Smiling in the face of complex problems
Collaborating and helping your fellow data engineers learn and grow
Working seamlessly across a variety of technical stacks, including Databricks, Snowflake & AWS

You might also have...
A Master's or other advanced degree in data science or a related field
Hands-on experience with one or more ecosystem technologies (e.g., Spark, Databricks, Snowflake, AWS/Azure/GCP)
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 and MLflow experience

Why phData? We offer:
A casual, award-winning small-business work environment
A culture that prizes autonomy, creativity, and transparency
Competitive compensation, benefits, PTO, and perks
Opportunities to learn new technologies and skills (e.g. extensive training and paid certifications)
The chance to work with and learn from a team of great people at the top of the machine learning and data engineering fields

Keywords: phData, Seattle , Machine Learning Architect, Professions , Seattle, Washington