Machine Learning Engineer

Location: San Francisco
Job Type: Permanent
Discipline:
Salary: Negotiable
Contact: Brandon Tenda
Email: email Brandon
Reference: BBBH9287_1668101936
Posted: 28 days ago

Machine Learning Engineer

Our client provides software and business solutions to design, connect,
and operate energy storage systems ranging in size from residential to utility- scale, as well as
grid-tied, microgrid, and off-grid systems. Our client's suite of products creates an ecosystem where
project developers, OEMs, financiers, and project operators can deploy advanced energy
projects using a seamless hardware-agnostic software platform.

Our client is a subsidiary of one of the world's largest and most recognized
photovoltaic manufacturers for its high-performance, high-quality solar cells and modules.


Job Summary

Our client is looking for an enthusiastic Machine Learning Operations (ML
Ops) Engineer who is eager to work at the forefront of the rapidly expanding energy storage
industry. As a ML Ops Engineer, you will be supporting the deployment and maintenance of our
forecasting algorithms, which are central to our client's software. This position sits within our client's Data
Science team.

Responsibilities

* Build and maintain robust ML pipelines.
* Collaborate with data scientists, software engineers and DevOps to deploy forecasting
algorithms into production.
* Implement monitoring systems to track how models are performing.
* Work to continuously improve model performance and debug where necessary.
* Manage the memory and computational footprint of our algorithms.
Required Experience & Skills
* A solid foundation in computer science and software engineering principles, including
object-oriented programming.

* Experience writing clean, maintainable, efficient and thoroughly tested python (3.6+)
code.
* Familiarity with machine learning algorithms, concepts and workflows.
* Experience working with ML libraries and packages such as sklearn, Keras and
Tensorflow.
* Ability to work collaboratively with all levels and teams

* Self-sufficient and proactive approach.
* Willingness to learn and adapt in the rapidly growing energy industry.
Desired Experience & Skills
* Knowledge of energy storage applications and renewable energy.
* Experience with available pipeline and monitoring tools for machine learning.
* Experience in the following technologies:
* Docker, Kubernetes, AWS
* Kafka streams
* Prometheus, Grafana
* PostgreSQL, Django ORM, Cassandra, Timescale DB, Redis, S3

Benefits

* Make a difference: join a group of people who are passionate about renewable energy
* Work with a small, dynamic and collaborative team
* Exposure to business models and technologies that are transforming worldwide
electricity markets and grid operations
* Convenient location in San Francisco (although almost entirely remote for now).