Machine Learning Engineer
San Francisco, CA, USA
Posted on Friday, January 27, 2023
This is a San Francisco based position that is currently remote and will have a hybrid schedule once we return to office. We are open to candidates willing to relocate to the San Francisco Bay Area.
Geli (Growing Energy Labs, Inc.) 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. Geli’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.
Geli is a subsidiary of Hanwha Q CELLS, one of the world’s largest photovoltaic manufacturers most recognized for its high-performance, high-quality solar cells and modules.
Geli is committed to helping make the planet a cleaner, better place to live, both with our software products and through our everyday actions.
Imagine a world where there is less reliance on non-renewable power, where you source your electricity from your neighbors rather than from power stations hundreds of miles away and software makes the best possible use of the solar, wind, and battery storage available. This is our vision.
We are looking for enthusiastic colleagues that are not only fluent in technology, but also share our vision of a world running on 100% renewable energy.
ABOUT THE JOB
Geli (Growing Energy Labs, Inc) is looking for an enthusiastic Machine Learning Engineer who is eager to work at the forefront of the rapidly expanding energy storage industry. As an ML Engineer, you will be supporting the deployment and maintenance of our forecasting algorithms, which are central to Geli’s software. This position sits within Geli’s Data Science team.
- 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
- Minimum 2 years experience as ML Engineer, Software Engineer, Data Scientist or Data Engineer
- AWS Experience: Proficient in at least one of Athena, DynamoDB, Lambda, Step Functions, SageMaker, SageMaker Studio, SageMaker Endpoints
- ML Tools: Proficient in at least one of MLflow, Weights & Biases, Docker (image creation and containerization), Kubeflow, DVC, Datadog, Grafana
- Data Science Skills: Strong understanding of supervised & unsupervised learning and performance metrics
- Programming skills: Proficient in both Python (object-oriented programming) and SQL
- Python libraries: Pandas, Sklearn
DESIRED EXPERIENCE & SKILLS
- Data Science Skills: Time-series forecasting.
- Nice to have Python libraries: TensorFlow, PyTorch, XGBoost, LightGBM, NumPy, SciPy, Statsmodels
BENEFITS OF WORKING AT GELI
Competitive salary commensurate with experience
Competitive benefits offerings
Conveniently accessible location in downtown San Francisco
Flexible work-from-home-office opportunities, as determined by the position and job duties
Cigna and Kaiser options - available by region
Cigna Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Cigna medical plan
Company-paid Basic Life, AD&D, short-term, and long-term disability insurance
Voluntary benefits include: critical illness, hospital indemnity, accident insurance
401(k) with a 4% employer match
3 weeks of paid Parental Leave
Sick time- 72 hours frontloaded per calendar year
Vacation time (Flex time), and 13 Paid Holidays
Health Advocate wellness and concierge services
Wellness programs with our benefits providers
Bereavement leave- 5 paid days
Make a difference: join a group of people who are passionate about renewable energy
Have an impact: the company is still small enough that everyone’s contribution has a significant impact on the success of the company
Many opportunities to lead teams, and projects, and contribute to development
Casual professional working environment: there’s no need to dress up, just present your best self
Work collaboratively in a diverse environment- we commit to reaching better decisions by respecting opinions and working through disagreements
We value the insights that a diverse team can bring. We encourage applications from members of groups that have been traditionally underrepresented in tech.
Growing Energy Labs, Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.