Senior Machine Learning Engineer

February 26

Apply Now

Receive Emails with Similar Jobs

GoodLeap

WebsiteLinkedInAll Job Openings

GoodLeap is a tech company delivering best-in-class financing and software products for sustainable solutions. It supports homeowners and businesses nationwide by providing solar loans, energy efficiency loans, and other financing solutions to promote green energy adoption. GoodLeap is committed to a sustainable future, having facilitated $58B in cumulative financing and offsetted 14M metric tons of CO2. The company offers solutions like solar and storage systems, energy-efficient upgrades, and smart home technologies, primarily catering to the green energy sector. Their partnerships and initiatives aim to expand access to clean energy and support environmental sustainability.

Clean energy financing • solar loans • Fintech • mortgage loans

501 - 1000 employees

Founded 2020

💸 Finance

⚡ Energy

💳 Fintech

📋 Description

• GoodLeap is a technology company delivering best-in-class financing and software products for sustainable solutions. • Senior Machine Learning Engineer will work closely with engineering tech leads to deploy LLM models into production, build scalable ML infrastructure, and optimize ML workflows. • This role will play a crucial role in defining and scaling ML/AI applications in production, ensuring efficiency, reliability, and automation across model development, training, and evaluation. • GoodLeap supports nonprofit, GivePower, building life-saving water and clean electricity systems.

🎯 Requirements

• Master’s degree in computer science, Machine Learning, or a related field with 5+ years of experience as an ML Engineer or ML Scientist in an industry setting. • Strong programming skills in Java, Python, and SQL/MySQL. • Hands-on experience in ML Ops, including large-scale ML applications, services, pipelines, and architectures. • Solid understanding of system design for ML systems, including design patterns, OOD (Object-Oriented Design), and interface design. • Experience with distributed processing architectures and ML/data workflow management platforms (e.g., Spark, Databricks, Airflow, Kubeflow, MLflow). • Experience with containerization and orchestration tools like Docker and Kubernetes • Preferred Qualifications: Ph.D. in Computer Science, Machine Learning, or a related field, or 3+ years of ML Engineering experience in addition to a Master’s degree. • Strong theoretical and practical understanding of machine learning models and frameworks (Scikit-Learn, TensorFlow, PyTorch, etc.). • Experience working with cloud-based solutions, especially AWS and Databricks. • Experience with CI/CD pipelines, automated testing, and test-driven development for ML applications. • Knowledge of microservice architectures and best practices for RESTful web services.

🏖️ Benefits

• In addition to the above salary, this role may be eligible for a bonus.