We are looking for someone who is passionate about technology, with a track record of success in building and supporting complex digital solutions. You should have a strong understanding of end-to-end machine learning lifecycles as well as proficiency in deploying natural language processing solutions at scale. You should also be a collaborative team player, with excellent communication skills and the ability to work effectively with cross-functional teams.
This is a full-time position with the opportunity to work hybrid in our office in Berlin.
Apply your knowledge and expertise in data processing, refinement and natural language processing (NLP) techniques that leverage our unique firmographics data
Implement innovative, scalable machine learning models that can be used in productionÂ
Build and own end-to-end machine learning lifecycle from data exploration, design, training, and testing to model deployment and metric monitoring.Â
Be a self-starter, eager to learn, and motivated by a passion for developing the best possible solutions to problems. This includes encouraging  best practices in engineering with regards to design and coding.
Closely collaborate with a talented cross-functional team of other machine learning, data science, MLOps, and software engineers to bring your models to life.
Completed bachelor’s or master’s degree in computer science, computational linguistics, statistics, engineering, or a related field
e.g. Deployment technologies: FastAPI, Flask, grpc microservices, Kubernetes K8s
Strong proficiency in Python and common ML frameworks and tools, libraries, data structures, and data modelingÂ
Experience working with large language models (LLMs): prompt engineering, fine-tuning and language model programming.Â
Stay up-to-date with state-of-the-art NLP breakthroughs, models, and architecturesÂ
Hands-on experience working with vector databases (e.g., Weaviate, Milvus, Qdrant)Â
Experience with knowledge graphs (RDF or property graphs)
The successful candidate is proactive, self-motivated, and adaptable, thriving in a fast-paced startup setting with a strong passion for technology. Committed to continuous learning and improvement, they excel in communication, end-to-end thinking, and collaboration, enabling effective work with cross-functional teams.
High level of responsibility and autonomy: You will have the opportunity to take ownership of projects and initiatives with the support of a collaborative team and a steep learning curve to develop your skills further.
Generous educational budget: We are committed to investing in our employees’ professional development and provide a generous educational budget to support your personal career goals.
Flat hierarchies and short decision paths: Our organizational structure is designed to promote collaboration, innovation, and fast decision-making, with a flat hierarchy and short decision paths.
Generous paid time off: We believe in the importance of work-life balance and offer five weeks of paid vacation each year, in addition to public holidays.
Flexible working arrangements: We recognize the value of flexibility and offer flexible working hours to support our employees’ diverse needs and lifestyles
We are looking for someone who is passionate about technology, with a track record of success in building and supporting complex digital solutions. You should have a strong understanding of end-to-end machine learning lifecycles as well as proficiency in deploying natural language processing solutions at scale. You should also be a collaborative team player, with excellent communication skills and the ability to work effectively with cross-functional teams.
This is a full-time position with the opportunity to work hybrid in our office in Berlin.
Apply your knowledge and expertise in data processing, refinement and natural language processing (NLP) techniques that leverage our unique firmographics data
Implement innovative, scalable machine learning models that can be used in productionÂ
Build and own end-to-end machine learning lifecycle from data exploration, design, training, and testing to model deployment and metric monitoring.Â
Be a self-starter, eager to learn, and motivated by a passion for developing the best possible solutions to problems. This includes encouraging  best practices in engineering with regards to design and coding.
Closely collaborate with a talented cross-functional team of other machine learning, data science, MLOps, and software engineers to bring your models to life.
Completed bachelor’s or master’s degree in computer science, computational linguistics, statistics, engineering, or a related field
e.g. Deployment technologies: FastAPI, Flask, grpc microservices, Kubernetes K8s
Strong proficiency in Python and common ML frameworks and tools, libraries, data structures, and data modelingÂ
Experience working with large language models (LLMs): prompt engineering, fine-tuning and language model programming.Â
Stay up-to-date with state-of-the-art NLP breakthroughs, models, and architecturesÂ
Hands-on experience working with vector databases (e.g., Weaviate, Milvus, Qdrant)Â
Experience with knowledge graphs (RDF or property graphs)
The successful candidate is proactive, self-motivated, and adaptable, thriving in a fast-paced startup setting with a strong passion for technology. Committed to continuous learning and improvement, they excel in communication, end-to-end thinking, and collaboration, enabling effective work with cross-functional teams.
High level of responsibility and autonomy: You will have the opportunity to take ownership of projects and initiatives with the support of a collaborative team and a steep learning curve to develop your skills further.
Generous educational budget: We are committed to investing in our employees’ professional development and provide a generous educational budget to support your personal career goals.
Flat hierarchies and short decision paths: Our organizational structure is designed to promote collaboration, innovation, and fast decision-making, with a flat hierarchy and short decision paths.
Generous paid time off: We believe in the importance of work-life balance and offer five weeks of paid vacation each year, in addition to public holidays.
Flexible working arrangements: We recognize the value of flexibility and offer flexible working hours to support our employees’ diverse needs and lifestyles
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