Senior Machine Learning Engineer

About Frequenz

Frequenz is a vibrant technology company developing groundbreaking artificial intelligence solutions that enable the rapid transition towards a decentralized world of energy. Our open source developer platform allows customers to accelerate their path towards 100% renewable energy. We’re helping companies rapidly transition from being passive electricity consumers to becoming fully self-sustaining prosumers, capable of leveraging various renewable energy assets. We empower them to take matters into their own hands as they pursue a better future for us all.

We’re passionate about making the impossible possible by rethinking out-dated processes and questioning the status quo, while turning the electric grid upside down. For us, the edge is the future, and our journey has only just begun. We’re looking for people ready to dive in head first, but be warned: it will be a hardcore ride where each day everyone tells you what we aim to achieve isn't possible. If this challenge doesn’t deter you, then you may be a good fit… after all, saving the planet is no easy feat!

Together with our clients, partners, early adopters, and innovators, we’re developing a global, leading-edge, open source, AI electricity platform. Join us -  the planet needs your help!

Responsibilities

• Develop ML applications: Utilize and contribute to the Frequenz Open Source SDK and our developer platform to create machine learning models based on real-time market, microgrid, and environmental data, as well as operational constraints.
• Manage the entire ML lifecycle: Responsibility for the entire lifecycle from initial design through development, deployment, and ongoing optimization. Continuously test and analyze models under various conditions, making relevant adjustments.
• Implement efficient solutions: Leverage modern EDGE AI hardware and distributed computing systems cost-effectively. Architect and design applications, frameworks and API specification as part of the interconnected edge-cloud ecosystem. Actively participate in software development to bring models to production.
• Contribute to ML strategy and innovation: Identify new research areas, expand capabilities, and support the generation of novel intellectual property.
• Write specifications and documentation: Produce clear and concise application specs and white papers. 
• Lead technical initiatives: Guide and inspire the team to implement and deploy future solutions. Mentor team members on coding standards, feature engineering, and design techniques.
• ‍Stay updated with ML tools: Introduce new tools, frameworks, and processes to the team and business.

Qualifications

• Educational qualifications: Degree  in Science, Technology, Engineering, Mathematics, Statistics, Physics, or a related field.
• Machine learning: Strong understanding and hands-on experience with a range of ML methods, including deep neural networks, traditional models like tree-based and linear models, and online training models. Proficiency in ML libraries such as PyTorch, TensorFlow, or scikit-learn is required, with a special emphasis on time series forecasting.
• Model deployment: Demonstrated experience in deploying and successfully utilizing ML models is essential.
• Application development: Proficient in developing applications as a significant part of the role, requiring strong coding skills and the ability to integrate machine learning models into end-user applications.
• Python skills: Proficiency in Python for data preprocessing, analysis, and visualization. Strong experience with concurrent programming, particularly using asyncio, for developing real-time applications is highly valued.
• Algorithm design: Strong proficiency in data structure, algorithm design, and implementation of efficient code.‍
• Development Tools: Required proficiency in Git, Linux, and Docker.

Nice-to-have

• ‍Research: A strong personal research agenda with peer-reviewed publications in areas relevant to our projects.‍
• Community engagement: Active contributions to open source projects or participation in coding competitions, demonstrating advanced coding skills and collaborative teamwork.‍
• Industry knowledge: In-depth knowledge of the energy sector or algorithmic trading.‍
• Edge AI: Practical experience with deploying AI on edge devices, with a focus on developing and optimizing real-time applications.‍
• Distributed computing: Understanding of distributed computing frameworks like Spark, Dask, and Ray, with the capability to develop further expertise.

About You

• Mission-driven: Deeply committed to Frequenz's mission and values.
• Team player: Flexible, collaborative, and dedicated to delivering high-quality work.
• Proactive: Passionate about improving and implementing efficient, automated processes.
• Innovative: Driven by curiosity and first-principle thinking, with a focus on turning research into production-ready code.
• Integrity: Open to feedback, maintaining high ethical standards, and contributing to a respectful, transparent environment.‍
• Research-oriented: Excellent research and problem-solving skills, eager to learn and share new methods and techniques.

Our Company Culture & Value

• Strong emphasis on sustainability and environmental responsibility.
• Encouragement of innovation, creativity, and collaboration.
• Focus on responsibilities and adaptability, with less emphasis on fixed roles, fostering a culture of cross-functional teamwork and flexibility.
• Commitment to employee growth, development as well as mental and physical well-being.
• Active promotion of diversity, equity, and inclusion.

Benefits

At Frequenz you will experience…

• Making a difference with sustainability
• Competitive salary and participation in our virtual options program
• Remote work and flexible working hours
• Custom hardware and software setup
• High level of self-determination and flexibility
• International work environment
• Exceptionally dedicated team with no-ego attitude that focuses on the big problems

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