At John Deere, we run so life can leap forward. This powerful purpose is our promise to humankind that we will dream, design and deliver breakthrough products that sustain our world for generations to come. The world is counting on us to feed billions of people and build vital infrastructures in villages, towns, and megacities. We live up to the legacy our founder forged in a one-room blacksmith's shop nearly two centuries ago by creating a culture that brings out the best in all of us. A culture where great ideas thrive because every voice is heard.
Primary Location: United States (US)- Texas- Austin
Function: Data Science & Analytics
Title: Lead Machine Learning Operations Engineer - REMOTE- 76252
Your Responsibilities
***This position may be in Johnston, IA OR Austin, TX OR can be performed remotely per the hiring manager's discretion.This may be dependent on the successful candidate's background, experience, and proficiency***
As a Lead Machine Learning DevOps Engineer for John Deere, you will work with a team of data scientists to help drive and scale capabilities associated with integrating machine learning into sales and marketing processes. You will be collaborating on developing cutting edge utilities and software products within a team of like-minded ML DevOps engineers, data engineers and data scientists that will be used to:
Ideally you will have a degree or equivalent related work experience in the following:
At John Deere, you are empowered to create a career that will take you to where you want to go. Here, you'll enjoy the freedom to explore new projects, the support to think outside the box and the advanced tools and technology that foster innovation and achievement. We offer comprehensive relocation and reward packages to help you get started on your new career path. Click hereto find out more about our Total Rewards Package.
The information contained herein is not intended to be an exhaustive list of all responsibilities and qualifications required of individuals performing the job. The qualifications detailed in this job description are not considered the minimum requirements necessary to perform the job, but rather as guidelines.
An Equal Opportunity Employer, John Deere requires a diversity of people, perspectives and ideas to address the complex challenges of its global business. John Deere is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sex, age, sexual orientation, gender identity, status as a protected veteran, or status as a qualified individual with disability.
Job Segment: Engineer, Consulting, Outside Sales, Computer Science, Application Developer, Engineering, Technology, Sales
Primary Location: United States (US)- Texas- Austin
Function: Data Science & Analytics
Title: Lead Machine Learning Operations Engineer - REMOTE- 76252
Your Responsibilities
***This position may be in Johnston, IA OR Austin, TX OR can be performed remotely per the hiring manager's discretion.This may be dependent on the successful candidate's background, experience, and proficiency***
As a Lead Machine Learning DevOps Engineer for John Deere, you will work with a team of data scientists to help drive and scale capabilities associated with integrating machine learning into sales and marketing processes. You will be collaborating on developing cutting edge utilities and software products within a team of like-minded ML DevOps engineers, data engineers and data scientists that will be used to:
- Support data science R&D teams in scaling and automating production solutions
- Develop APIs to integrate machine learning models into business applications
- Scale and automate data pipelines, feature engineering pipelines, and model training/retraining pipelines
- Monitor and maintain machine learning models in production
- Provide coaching and mentoring to others within the technical discipline; be recognized as a technical advisor and creative problem solver
- Proven cloud-native software architecture experience employing containers, container orchestration, and distributed systems with platforms like AWS or MS Azure (4+ years)
- Proven software engineering experience in the design, development, testing and integration of advanced analytics and/or machine learning solutions (5+ years)
- Proven experience leveraging DevSecOps and lean development principles such as Continuous Integration and Continuous Delivery (4+ years)
- Proven experience employing the DevOps "left-shift" mentality by building systems with Infrastructure as Code (IaC)
- Proven experience in an Agile/Scrum team environment (4+ years)
- Strong understanding of applications development environment, database systems, data management and infrastructure capabilities and constraints (5+ years)
- Working understanding of full-stack design patterns and designing loosely coupled architectures (4+ years)
- Prior experience with delivering DataOps capabilities into production environments (e.g., automating data pipelines, feature engineering pipelines, model training/retraining pipelines)
- Prior experience with integrating advanced analytics models into operational business processes employing microservices based architectures
- Working knowledge with one or more of the following technologies:
- AWS MLOps Framework (Lambda, CodePipeline, API Gateway, CloudFormation) or Databricks/MLFlow
- DS-ML Platforms: Domino Data Labs, Databricks, DataRobot, AWS Sagemaker
- Data Management: Relational/SQL and non-relational/NoSQL(e.g. GraphQL) systems
- Background working for technology companies developing data-centric products
- Prior experience with developing frameworks to harvest intellectual property, embed best practices, and streamline operational processes to bring performance and scalability across the end-to-end model lifecycle (from data wrangling and feature engineering to algorithm experimentation and hyper-parameter tuning to model monitoring and model governance)
- Familiarity with one or more of the following technologies:
- MLOps: Seldon, Data Version Control (DVC), ModelDB
- Feature Stores: AWS Sagemaker, Databricks/Delta Lake + AutoML, Feast/Tecton, Molecula/Pilosa
- Skilled in interpersonal communications, collaboration, negotiation, and conflict resolution
- Ability to perform as a technical lead providing technical coaching and mentoring to others
- Proven consulting skills and experience, influence effectively, ability to resolve impediments in a timely manner
- Learning Agility / Innovative / Growth Mindset - desire and openness for continuous technical learning and identifying areas for application; willingness to deal with and thrive in uncertainty
Ideally you will have a degree or equivalent related work experience in the following:
- BS or MS in Computational Data Science, Computer Science, Data Science or related field of study
- Work experience should consist of a proven track record of efficiently designing, developing, and releasing machine learning products efficiently, predictably and sustainably, both independently and collaboratively over a 5+ year period.
At John Deere, you are empowered to create a career that will take you to where you want to go. Here, you'll enjoy the freedom to explore new projects, the support to think outside the box and the advanced tools and technology that foster innovation and achievement. We offer comprehensive relocation and reward packages to help you get started on your new career path. Click hereto find out more about our Total Rewards Package.
The information contained herein is not intended to be an exhaustive list of all responsibilities and qualifications required of individuals performing the job. The qualifications detailed in this job description are not considered the minimum requirements necessary to perform the job, but rather as guidelines.
An Equal Opportunity Employer, John Deere requires a diversity of people, perspectives and ideas to address the complex challenges of its global business. John Deere is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sex, age, sexual orientation, gender identity, status as a protected veteran, or status as a qualified individual with disability.
Job Segment: Engineer, Consulting, Outside Sales, Computer Science, Application Developer, Engineering, Technology, Sales