Machine Learning Engineer (Staff/ Sr. Staff)

What we are looking for

Equilibrium was founded with a vision for building a company where innovation, collaboration, machine learning, data science, and software engineering drive all aspects of our algorithmic decision-making. We are looking for ML engineers of all levels who are passionate to stay at the forefront of AI/ML technology and cloud engineering, leveraging cloud services, data science platforms, and automation pipelines for the operationalization of AI/ML-driven solutions at an enterprise scale. 

What you will do

• Design, build, implement, and support the ML Engineering platforms and tools underpinning our massive-scale ML pipelines and models
• Design and implement ML toolchains and data platforms to scale ML solutions in production
• Improve the ML infrastructure,  software, and tooling that underpin uses these models
• Build the libraries and frameworks that support our large-scale, complex ML pipelines
• Design, build, implement and support production ML pipelines and models
• Define and operate data handling routines to supply training data to training jobs
• Version the training data and record data, trained models, and quality parameters of these models
• Re-train and re-deploy models based on quality parameters collected in continuous monitoring
• Define and monitor quality parameters for ML models in production
• Shape and operate best practices for managing models in production
• Maintain a high-quality standard for all ML models in production
• Collaboratively innovate across a multi-functional technical team
• Proactively communicating with other team members and project stakeholders
• Work closely with data science teams to take over newly developed models into production, and advise data science teams if model redesign should be considered
• Contribute to and help improve the value addition of our computational science efforts
• Bring your data and ML science knowledge to bear in helping our computational science teams identify new techniques, tools, and approaches to improve the value add of EQ’s ML models
• Participate in cutting-edge research in artificial intelligence and machine learning applications

The minimum qualifications you’ll need

• A commitment to clean energy and combating climate change.
• Proficiency in software development with several years of experience, especially in Python.
• Hands-on experience with AWS cloud technologies (like API Gateway, ECS/EKS/Fargate).
• Familiarity with automated deployment and orchestration tools such as CI/CD, Docker, Metaflow, Feature Store, and Temporal.
• Proven experience in applying machine learning techniques to industrial datasets.
• Comprehensive understanding of data science QA methodologies and tools.
• Prior experience in operationalizing machine learning workflows.
• Agility in working with cross-functional teams and adapting to new work methodologies.
• Familiarity with agile practices, or a willingness to learn.
• Strong communication capabilities.

Nice to have additional skills

• PhD in computer science or a Bachelor's/Master's degree in computer science or machine learning
• Familiarity with programming in Golang and Julia.
• Experience in time series forecasting.
• Expertise in probabilistic forecasting.
• Background in the energy and power systems sector.