What we are looking for
We are looking for Software Engineers to contribute across our end-to-end platform. Our software engineers work across cloud infrastructure and distributed systems, data engineering, ML engineering and MLOps, simulation ecosystems, complex workflow orchestration, microservices mesh, application development and security. Our software engineers supercharge design and delivery of our product development activities while helping to build and lead an engineering capability that is the core of the company’s strategy and identity. If you want to fight climate change and love modern tech stacks, clarity of product vision, and exceptional colleagues, this role is for you!
In the near-term, you will work with other software engineers, data engineers, infrastructure engineers, ML engineers, data scientists, researchers and product managers to execute our ML- and AI-infused product development plan en route to growing our company. Have a specific interest in a particular part of our technical stack? No problem...we’re looking for technical leaders across our ecosystem.
In the medium-term, you will cultivate our software engineering function by nurturing a culture of experimentation and delivery. You will design, write and optimize software to support our end-to-end product development ambitions, helping to build the core of our competitive differentiation.
What you will do
- Lead the design, development, testing, delivery and support of software systems across our technical stack that drive our end-to-end product development ambitions.
- Cloud and distributed systems development - contribute to building and maintaining our cloud-native platform and infrastructure; K8s, cluster management, linux containers, etc.
- Data Platform and Engineering - our use cases are varied and so are our data engineering needs. From stream, batch, pub-sub, queuing, state stores, virtualization, complex data models and closed-loop pipelines, we’ve got a little bit of everything.
- ML Engineering and MLOps - we aim to infuse EVERY business process with ML and AI, relying on closed-loop decision-making at every valuable juncture.
- Simulation ecosystem - our ML- and AI-centric workflows need training and testing.
- Workflow orchestration - we live in the land of complex, autonomous, multi-step sequential workflows operating in a distributed runtime with low latency requirements.
- Service mesh - we rely heavily on reuse of core microservices to keep application development productivity high, which requires thoughtful service mesh management.
- Application development - we’ve just started designing and developing across our anchor product suites, each focused on leveraging a common platform and service core.
- DevSecOps - security is inherently embedded within our development and operations practices, and we leverage bespoke security techniques for some unique exposures.
- Assist in product development strategy, design, planning and productivity.
- Contribute your unique technical, user, and market knowledge to product strategy.
- Contribute to product and architectural design.
- Contribute to product roadmapping, resource planning and sprint management.
- Contribute to product development productivity improvements, including best practices, technical documentation, code reviews and automation / utility / abstraction packages.
- Serve as a member of our technical team across both engineering and research.
- Collaborate asynchronously with engineers, researchers and product managers across time zones to design, build and ship code.
- Contribute to technical strategy and planning across the company.
- Represent Equilibrium in external venues, including presenting work at conferences and contributing to open-source projects.
The minimum qualifications you’ll need
- Passion for clean energy and fighting climate change
- BS/Master's degree in a quantitative discipline (e.g., Computer Science, Operations Research, Industrial Engineering, Mathematics, Economics, Physics, Electrical Engineering) or equivalent practical experience.
- Software development experience in Python, Go, Julia, C, or Rust.
- 8 years of relevant work experience.
Nice to have additional skills
- PhD degree in a quantitative discipline (e.g., Computer Science, Operations Research, Industrial Engineering, Mathematics, Economics, Physics, Electrical Engineering).
- 8 years of relevant work experience, including expert software engineering fundamentals and experience building software to support ML and AI pipelines, and associated data structures.
- Expertise in Go, Python, C, Rust, or Julia. Experience with orchestration tools like Temporal.
- Advanced proficiency across a range of data engineering tools (ELT, streaming, pub-sub, relational DBs, object DBs, GraphDBs, etc.).
- Deep expertise across any one of our tech stack domains: cloud infrastructure, data platform and engineering, IOT, MLOps and ML pipelines, simulation ecosystems, workflow orchestration, microservices orchestration, and/or application development.
- Familiarity supporting and releasing ML/AI models that drive operational workflows (e.g., models that run and produce new inferences every hour of the day).
- Proactive communicator who can translate product design specs into organized code.
- Experience communicating the results of analyses with product, engineering, and leadership teams to influence product and engineering strategy.
- Demonstrated proactivity and self-direction. Willingness to teach as well as learn.
- Excellent team collaboration skills and collaboration-first mentality.
- Experience with trading systems.
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