Lead Machine Learning Engineer

Phoenix, AZ, USA (Remote)

Job Type

Data

Please note: This position has the possibility to work remotely up to 100% of the time. The position will require occasional travel to the Phoenix corporate offices and/or site locations . This position may be performed anywhere in the U.S. except California, Connecticut, New Hampshire, Massachusetts, Michigan, Illinois, Kentucky and New York. Additional states may be excluded from remote work based on business factors. Should the positions shift to in-office work in the future, the company will offer relocation benefits at that time should the position meet the established eligibility for these benefits.


Role Summary:

You will be a lead contributor on a fast-growing team pursuing a vision of analytics-driven mining. Your expertise in software engineering and machine learning will enable and empower the company’s data science team to build and deploy complex models and software systems to production. The company understands that its models do not reach their full potential until they become solutions consumable by the enterprise. You will work in close collaboration with mining operations, subject matter experts, data scientists, and software engineers to not only develop advanced AI and ML solutions but deploy and automate those solutions in production environments. You will be a champion of MLOps, DevOps, and agile practices; leading project teams and mentoring junior team members.

Essential Duties and Responsibilities:

  • Develop, productionize, and deploy scalable, resilient software solutions for operationalizing AI & ML

  • Adhere to software architecture and software design best practices to write scalable, maintainable, well-designed code. Champion of Object-Oriented Design Principles: DRY, SRP, Open Closed, Liskov Substitution, Dependency Inversion, Interface Segregation, DelegationIn collaboration with Data Engineering design and build feature engineering pipelines for extraction, transformation, and loading of data from a variety of data sources for ML models.

  • In collaboration with Data Engineering and Data Scientists, build CI/CD pipelines that automate code quality checks and deployment actions

  • Stay current on new developments in ML frameworks, data structures, data modelling, software architecture and libraries available for solution development

  • Coach data scientists and data engineers on software development best practices

  • Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions. Proactively participate in problem solving sessions and the scrum process to ensure delivery of business objectives. Acts as a facilitator of complex technical topics that require cross-functional consultation.

  • Act as a positive coach/mentor for broader organization to develop stronger understanding of software architecture and software design patterns that create scalable, maintainable, well-designed analytics solutions. Proactively seek out opportunities to learn new skillsets and understand how they can be applied to the company’s analytics practice.

Qualifications:

  • Bachelor’s degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and five (5) years of relevant work experience; OR

  • Master’s degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and three (3) years of relevant work experience; OR

  • Ph.D. in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and one (1) year of relevant work experience

  • Strong experience in at least two areas below:

Proficient practitioner of Python development with experience designing high quality, production Python codebases
Proficient practitioner in software and ML systems architecture
Experience applying software development best practices into machine learning projects, including DevOps CI/CD, Release Management, and Test-Driven Development using Python and SQL
Data science experience wrangling data, model selection, model training, modeling validation, e.g., Operational Readiness Evaluator and Model Development and Assessment Framework, and deployment at scale
Experience with Agile and DevOps software development principles/methodologies, keep team focus on deliver business value
Experience leading and developing teams

  • Experience with Edge Analytics, embedded systems, or computer vision.

  • Experience with Databricks and Azure cloud suite with emphasis on ML tools.

  • Experience working in Data Architecture, engineering and ETL teams, managing Design, Implementation of projects that utilize big data, advanced analytics and machine learning technologies.

  • Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking to large audiences.

  • Strong verbal and written skills in English language.


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