As a Senior ML Field Engineer at Apheris, you will be working with us to develop and commercialize our Apheris Compute Gateway – a software product that enables ML Engineers to build models on distributed and sensitive data using federated learning. You will work as part of our commercial & pre-sales team with prospective customers at a technical level, evaluating their needs and demonstrating how our product meets them. These may involve complex enterprise setups where organizations securely collaborate on AI across boundaries. You will also work closely together with our product and engineering teams to build prototypes and POCs that will help us accelerate our deals. We would also like you to build a presence for Apheris in the wider community by attending and presenting at workshops and conferences, and further activities to help build a developer community around our product.

• Engage with prospective customers to understand their technical requirements, pain points, and business objectives. Use this information to craft and deliver tailored product demonstrations that showcase the benefits of Apheris' offerings.
• Serve as the primary technical resource for the commercial & pre-sales team and prospective customers, demonstrating in-depth knowledge of the Apheris product and its capabilities.
• Lead and manage proof-of-concept projects and pilots with prospective customers.
• Collect and relay customer feedback to the product management and development teams, contributing to continuous product improvement and innovation.
• Act as an evangelist for the Apheris product by promoting its value and benefits at conferences, webinars, meet-ups and other events. Develop and deliver thought leadership content such as blog posts and case studies to showcase innovative use cases. Build strong relationships with the community to enhance the visibility and reputation of Apheris.

• 5+ years of relevant working experience, or a Bachelor / Master / PhD in Computer Science or related fields (e.g., Physics, Mathematics, Engineering) and 2+ years of relevant working experience
• Experience working in a in a commercial/pre-sales team for enterprise scale Data, AI and ML solutions in combination with state-of-the-art MLOps
• Deep understanding of the full lifecycle of an ML solution (incl. related ML tooling/infrastructure) and how it can fit in a business process to make real impact
• Deep understanding of advanced analytics, machine learning and deep learning workflows, and industry experience with relevant frameworks (e.g., Pandas, PyTorch)
• Strong experience in Python programming. Further programming languages are a plus (e.g., R, Go, Rust, JavaScript)
• Experience with cloud technologies and providers (preferably AWS)
• Enthusiasm and experience in working directly with prospective customers on their problems and needs much of the time, supporting commercial teams in a technical capacity and contributing to successful sales outcomes
• Passionate about continuous learning, demonstrated agility in quickly adopting and mastering new technologies
• Excellent communicator: you are fluent in English (verbal and written) and communicate in a constructive and proactive manner - enabling you to demo and explain our product to different kind of stakeholders ranging from C-Level Executives to Applied Data Science Users
• Confident to take ownership of a problem, gather ideas to solve it and convey your approach efficiently
• Genuine interest in working with cutting-edge technology in a fast-paced environment and a young start-up
• Enthusiasm for working in a remote-first company, with willingness to travel up to 20%

• Experience in operationalization of ML, from using open source frameworks (e.g., MLflow, Kubeflow) to managed services / cloud provider offerings (e.g. AWS Sagemaker, Google AI Platform, Azure Machine Learning, Databricks, DataRobot, …) to specific on-prem solutions (e.g., Dkube)
• Understanding of and experience with Healthcare and Life Sciences use cases
• Experience with using multiple cloud providers (e.g., AWS, Azure, GCP, OpenStack) and on-premise setups (e.g., locally hosted Kubernetes)
• Experience with enterprise-level customers, their security and compliance requirements, and ML enterprise platforms they may use (e.g., Databricks, Domino Labs)
• Experience with distributed/federated systems
• Experience with AI governance, regulation, security and privacy

• Industry-competitive compensation
• Early-stage equity
• Remote-first working – work where you work best, whether from home or a co-working space near you
• The right hardware to make you efficient – be it a laptop with Linux, Windows or a MacBook
• Great suite of benefits including a wellbeing budget, mental health benefits, a work from home budget, a co-working stipend and a learning and development budget
• Regular team lunches and social events
• Generous holiday allowance (location-dependent)
• Quarterly All Hands meet-up (usually at our Berlin HQ should you choose to join in)
• A fun and diverse team of mission-driven individuals with a drive to see AI and ML used for good
• Plenty of room to grow personally and professionally and shape your own role

Here’s a bit more about our culture and ambitions at Apheris!

Finding solutions to the planet’s most urgent problems requires organizations to collaborate. But the data and insights needed to solve these challenges are locked away in businesses, unable to be centralized or directly shared for collaboration with customers and partners.
Apheris is pioneering a new way for organizations to securely collaborate on even the most sensitive data across organizational and geographical boundaries. By unlocking value from sensitive data, Apheris is accelerating discovery and innovation, driving operational efficiency, and reducing risk and carbon impact for our customers and their partners.
Apheris was founded in 2019 after our co-founders built data applications that couldn't be used as data was distributed across departments and couldn’t be shared or centralized as a result of regulation. From this they got thinking: what if the data didn’t have to move and instead the computation was sent to the data? Fast-forward to today, Apheris is a platform that empowers businesses to run advanced analytics and machine learning models across organizational and geographical borders in a way that’s secure, private, and governed. By powering their data infrastructure with federated ML and analytics, they are able to build and operationalize data applications in ways previously not possible.
At Apheris, we’re unified by our mission and the positive impact we can have. We’re excited by the potential we can bring with our federated approach and are looking for the next addition to our marketing team to join us in realizing our mission.

Our interview process is split into three phases:

1. Initial Screening: If your application matches our requirements, we invite you to an initial video call to explore the fit. In this 30min interview, you will get to know us and the role. The interviewer will be interested in your relevant experiences and skills, as well as answer any question on the company and the role itself that you may have.

2. Deep Dive: In this phase, domain experts from our team will assess your skills and knowledge required for the role by asking you about meaningful experiences or your solutions for specific scenarios in line with the role we are staffing.

3. Final Interview: Finally, we invite you for up to three hours of targeted sessions with our founders, talking about our culture and meeting future co-workers on the ground.