Top Zurich Jobs

Gravis Robotics is a startup that turns heavy construction machines into intelligent and autonomous robots.  Our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of machines in a gamified environment—from anywhere in the world.  Our team has over a decade of academic experience honing the cutting edge of large-scale robotics, and is rapidly growing to bring that expertise into a trillion dollar industry through active deployments with market leaders.

About the Job

At Gravis, we make the heaviest machines move through dirty and dynamic environments with style and grace, by leveraging advanced learning-based methods for planning and control.  We are looking for a motivated software engineer with a background in deep reinforcement learning to augment our team, and to help teach our machines the art of moving mountains.  In this role, you will contribute to developments that improve a range of activities, from high-level task planning to navigation and control.

Qualifications

• University degree in Computer Science, Robotics, or a related field
• Proficiency with C++, Python, and Git
• Experience with large-scale robotics simulation, sim-to-real transfer
• Experience with synthetic data generation and augmentation
• Familiarity with popular deep learning libraries (TensorFlow, PyTorch, etc.) and  ROS/ROS2
• Expertise in algorithm tuning and optimization (reward shaping, hyperparameter tuning, etc.)
• Experience with hardware deployment, beneficial

This is an opportunity to join a dynamic and versatile team, and to be part of a young startup that will revolutionize heavy construction.  Gravis Robotics offers a fair market salary and a working location in the vibrant heart of Zurich.  As a forward-facing startup, we understand that work-life balance and flexibility are important considerations for many professionals:  If you are a highly qualified candidate with the requisite skills and experience, we encourage you to apply and discuss your preferred working arrangement during the interview process.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based upon race, color, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

We are an international team that is working to solve problems with a global impact:  to facilitate efficient communication and collaboration, proficiency in English is a requirement for all roles.

About us:

Daedalean is a Zürich-based startup founded by experienced engineers who want to completely revolutionize air travel within the next decade. We combine computer vision, deep learning, and robotics to develop full “level-5” autonomy for flying vehicles, both existing aircraft and the electric VTOLs that you may have seen in the media.

Your role:

In collaboration with our team of engineers, machine learning researchers and certification experts, prove performance guarantees of safety-critical aviation systems based on machine learning.

Areas of the work include:

• Generalization bounds for deep neural networks.
• Data completeness and correctness (high-dimensional data), impact analysis of distributions shift.
• Robustness in development and operations (input and data robustness).
• Analysis of dynamical systems and their filtering.
• Monte-Carlo analyses based on complex statistical models (e.g. Bayesian networks).
• Statistical hypothesis testing.

• PhD degree in theoretical Machine Learning.
• Proven experience in the domain of probability, statistics.
• Hands-on experience with Machine Learning in the industry setting.
• Creativity as we work on problems that no one has solved before.

• A team of experienced engineers and researchers, who joined us from most recognized companies and institutions.
• Difficult and interesting problems to solve. 
• Test flights in the Swiss Alps for you to join.
• Stock options.
• Pilot license subsidy.
• Hybrid work setting.
• Learning & Development budget: visit conferences of your choice.
• Gym membership.

Observe is building a multi-tenant SaaS product in the Observability space. The core of the product is a novel data management platform that combines stream processing and a temporal-relational data model, implemented on top of a cloud data warehousing platform (Snowflake).

As a data-driven company, we track and collect statistics for each of the millions of queries we run each day. To fully harness our platform’s potential, we need to improve our query costing to be able to accurately predict resource demands and maximize our resource utilization and predict shifts in our workload and our underlying platform’s performance.

The ideal candidate for the Machine Learning Engineer role has a strong track record of applying machine learning techniques to solve real world problems and can quickly implement such models and prototype necessary data pipelines.

Ideal Candidate Profile

• Masters or PhD in a relevant field, e.g., in Computer Science / Mathematics
• 5+ years of relevant software engineering experience
• 3+ years of hands-on Machine Learning experience with at least two of the following techniques: (a) learning stochastic processes such as hidden Markov models or Gaussian processes; (b) AI planning and/or reinforcement learning in Markov decision processes; (c) inference techniques such as Bayesian network; (d) ensemble learning techniques such as random forests
• hands-on experience in neural networks is a plus, but not required
• principles of relational data management or stream processing useful for context

We offer remote work possibilities for exceptional candidates.

Fluence (Nasdaq: FLNC) is a global market leader in energy storage products and services and digital applications for renewables and storage. With a presence in 30 global markets, Fluence provides an ecosystem of offerings to drive the clean energy transition, including modular, scalable storage products, comprehensive service offerings, and the Fluence IQ platform, which delivers AI-enabled digital applications for managing and optimizing storage and renewables. The company is transforming the way we power our world by helping customers create more resilient and sustainable electric grids. For more information, please visit fluenceenergy.com.

OUR CULTURE AND VALUES

We are guided by our passion to transform the way we power our world. Achieving our goals requires creativity, diversity of ideas and backgrounds, and building trust to effect change and move with speed.

We are Leading

Fluence currently has thousands of MW of energy storage projects operated or awarded worldwide in addition to the thousands of MW of projects managed by our trading platform—and we are growing every day.

We are Responsible

Fluence is defined by its unwavering commitment to safety, quality, and integrity.

We are Agile

We achieve our goals and meet our customer’s needs by cultivating curiosity, adaptability, and self-reflection in our teams.

We are Fun

We value the diversity in thought and experience of our coworkers and customers. Through honest, forthcoming, and respectful communications we work to ensure that Fluence is an inclusive and welcoming environment for all. 

This position will be within the Fluence Digital business unit, formed following Fluence’s acquisition of San Francisco-based start-up AMS. Fluence Digital’s IQ platform uses artificial intelligence, advanced price forecasting, portfolio optimization and market bidding to ensure energy storage and flexible generation assets are optimally participating in wholesale electricity markets.

ABOUT THE POSITION:

This position will be within the Fluence Digital business unit. Fluence Digital’s software technology uses fully automated data acquisition, analysis and computational algorithms powered by artificial intelligence.

As Data Scientist, you will develop data-driven monitoring and analysis solutions for renewable energy plants located across the globe, with particular focus on Battery Energy Storage Systems. You will be able to understand the operational aspects of these assets and to identify performance issues. For this purpose, you will handle big data volumes and you will extract clear insights, also leveraging machine-learning techniques and physical modelling. Collaborating with Software Engineering team for the development of new software modules and building relationships with Clients are important responsibilities for this role.

The role will be based in Fluence Digital’s Zürich office and will report into the Data Science & Product team, with close interaction with software engineers, product managers, and subject matter experts to shape the evolution of our company and the future of the renewable assets’ performance management and optimization landscape.

Key responsibilities include:

·       Analyze Battery Energy Storage Systems performance

·       Develop analytics and optimize data analysis tools

·       Technical support to clients

·       Work with Software Engineering to develop new modules and functionalities

What will our ideal candidate bring to Fluence?

•     MSc in Mechanical or Electrical or Chemical Engineering
•     Must have academic and/or work experience with battery storage technology
•     Knowledge of cell chemistry and experience with cell modelling is required
•     Proven programming skills with Python
•     Experience with data analysis and visualization tools
•     Knowledge of statistical analysis and machine learning algorithms
•     Team player with excellent communication skills
•     Strong attention to detail
•   Proven ability to meet deadlines and deliver solutions quickly at high quality
• Passionate about learning, and tackling new and exciting technical challenges

•     Python
•     BI tools
•    SQL
•   MS Office
•    Linux

Follow Fluence on LinkedIn:  Fluence LinkedIn

Fluence Career Page: Fluence Careers

Fluence IS AN EQUAL OPPORTUNITY EMPLOYER and fully subscribes to the principles of Equal Employment Opportunity to ensure that all applicants and employees are considered for hire, promotion, and job status without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, marital or familial status.