- Lead Machine Learning projects end-to-end and develop platform tooling for the Data Science team.
- Work with data scientists to understand their data needs and put together data pipelines to ingest data.
- Work with data scientists to take data science model prototypes to production.
- Mentor and train junior team members.
- Enhance and improve the code deployment and model monitoring frameworks and project operations documentation.
- Design, provision and maintain the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations.
- Write high quality code that has high test coverage.
- Participate in code reviews to help improve code quality.
- Work closely with IT to stay up to date on upcoming changes to National Grid's infrastructure.
- Technologies/Tools we use: Python, SQL, Azure (Virtual Machines, Azure Web Apps, Cloud Storage, Azure ML), Anaconda packages, Git, GitHub, GitHub Actions, Terraform, Artifactory, Airflow, Docker, Kubernetes, Linux/Windows VMs.
- At least 7 years of hands-on experience implementing AI/ML solutions and platform tooling for Data Science.
- Expert in Python which includes experience in libraries such as Pandas, scikit-learn and proficient in SQL.
- Knowledge of best practices in software engineering is necessary.
- At least 3 to 5 years of hands-on experience in some combination of the following technologies: Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell scripting (primary Bash but PowerShell as well).
- A solid understanding of modern security and networking principles and standards.
- A foundational knowledge of Data Science is strongly preferred.
- Bachelor's or higher degree in Computer Science, Data Science, and/or related quantitative degree is preferred from an accredited institution.
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Lead Machine Learning Engineer - Brooklyn, United States - National Grid USA
Description
About usNational Grid is hiring a Lead Machine Learning Engineer, Data Science. The position can be located in Waltham, MA or Brooklyn, NY. Every day we deliver safe and secure energy to homes, communities, and businesses. We are there when people need us the most. We connect people to the energy they need for the lives they live.
The pace of change in society and our industry is accelerating and our expertise and track record puts us in an unparalleled position to shape the sustainable future of our industry.
To be successful we must anticipate the needs of our customers, reducing the cost of energy delivery today and pioneering the flexible energy systems of tomorrow.
This requires us to deliver on our promises and always look for new opportunities to grow, both ourselves and our business.
Job Purpose
As a Lead Machine Learning Engineer on the National Grid Data Science team, you will develop data pipelines, take data science prototype models to production, fix production bugs, monitor operations and provision the necessary infrastructure in Azure.
US Colleagues must reside within our existing footprint, which includes contiguous states (New Jersey, Pennsylvania, Connecticut, New Hampshire, Maine, Rhode Island, and Vermont).
A hybrid worker should also reside within a reasonable, commutable distance to their assigned primary office.Key Accountabilities
Salary
Waltham:
$143k - $168k a year
Brooklyn:
$153k - $180k a year
This position has a career path which provides for advancement opportunities within and across bands as you develop and evolve in the position; gaining experience, expertise and acquiring and applying technical skills.
National Grid is an equal opportunity employer that values a broad diversity of talent, knowledge, experience and expertise. We foster a culture of inclusion that drives employee engagement to deliver superior performance to the communities we serve. National Grid is proud to be an affirmative action employer. We encourage minorities, women, individuals with disabilities and protected veterans to join the National Grid team.
Minimum Salary:
Maximum Salary:
Salary Unit:
Yearly
