AI Engineer for AI Startup für Potsdam gesucht
Arbeits- und Stellenangebot im Regiobizz Arbeitsmarkt
Job Kategorie: IT/IT-Dienstleistung Informationstechnologie (IT)
Stellenangebot Basisdaten
- Arbeitsort:
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DE 14482 Potsdam
- Umkreis:
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keine Angabe.
- Art der Arbeitsstelle:
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- Letze Aktualisierung:
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13.11.20242024-11-13
Stellenausschreibung: AI Engineer for AI Startup
- Arbeitgeber bzw.
Arbeitsvermittler
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Rhesis AI GmbH in Hamburg
- Branche
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IT/IT-Dienstleistung
- Kategorie
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Informationstechnologie (IT)
- Stellenbeschreibung
- Intro Join us at Rhesis AI – Ensuring Gen AI applications deliver
value, not surprises! At Rhesis AI, we empower organizations to
develop and deploy Gen AI applications that meet high standards for
reliability, robustness, and compliance. Our testing platform helps AI
teams to validate and secure Gen AI applications across diverse use
cases and industries, ensuring they perform predictably, adhere to
restrictions, and meet client expectations. If you’re passionate
about advancing trustworthy AI that responsibly serves humanity, we
invite you to join our mission. Tasks What you will do: Oversee and/or
execute the design, development, fine-tuning, and deployment of large
language models and generative AI systems for the Rhesis AI platform.
Implement LLMOps best practices to streamline the machine learning
lifecycle from data ingestion to model deployment and continuous
improvement. Drive research and development to replicate
state-of-the-art ML models and papers, as well as carry out
independent research efforts (yes, you can publish!). Develop
LLM-enabled data pipelines using tools job orchestration tools to
integrate large-scale language models into data workflows. Collaborate
with cross-functional teams to integrate AI solutions into existing
systems and processes. Stay updated on the latest advancements in AI,
ML, and NLP to inform strategic decision-making and product
innovation. Lead research efforts to ensure compliance with regulatory
requirements and ethical standards in AI development and deployment.
While your role will be primarily focused on artificial intelligence
and machine learning, you will occasionally contribute to data
engineering, MLOps, and general software engineering tasks as needed
by the team. As part of a small and dynamic team, you will be expected
to pitch in where necessary and collaborate across disciplines to help
build and enhance the product. Requirements You are great for this
role, if you have: Important Skills Hands-on experience with Large
Language Models and Generative AI Strong background in Python
programming, ML frameworks (JAX, PyTorch, TensorFlow, HuggingFace
Transformers, Scikit-Learn), and MLOps expertise. Knowledge of ML
fundamentals and software engineering best practices, such as testing.
Experience in the development of robust, production-ready code.
Proficiency in CI/CD, DevOps pipelines, and containerization.
Experience in Natural Language Processing. Awesome Skills Experience
with research, development and/or replication of state-of-the-art ML
models / papers Experience with infrastructure automation (e.g.,
Infrastructure as Code). Building near-real-time and real-time data
pipelines (e.g. Kafka) Working with data intensive pipelines (e.g.
using Spark and/or Databricks) Knowledge of cloud-native solutions
(GCP, Azure, AWS) Building and fine-tuning deep learning models for
deployment and inference Overall skills Solid software engineering
skills with the ability to design sophisticated software systems,
curate datasets, and train models for scientific applications.
Proficiency in Python programming and developing production-ready code
for data-driven applications. Expertise in system design and
problem-solving, including the ability to decompose complex problems
into simpler solutions. Familiarity with modern development practices
and tools such as version control, CI/CD, containerization, and
cloud-native solutions (e.g., Azure or AWS). Experience in building
real-time data pipelines, natural language processing, container-based
development, and infrastructure automation. Previous roles as a Senior
Machine Learning Engineer with MLOps experience, optimizing and
deploying deep learning models. In summary, the candidate should have
a strong background in both machine learning and software engineering,
with specific expertise in developing and deploying advanced machine
learning models, along with a solid understanding of modern
development practices and tools. Benefits We’re excited to offer a
fixed one-year contract (initially, with likely extension), starting 1
February , along with a range of benefits to support our team members,
including: Comprehensive compensation package including shares: We
offer salaries and benefits tailored to your experience and
qualifications, along with the opportunity to gain ownership in the
company. Professional development opportunities: We provide resources
and support for ongoing learning and career growth, including access
to training programs, workshops, and conferences. Flexible work
arrangements: We understand the importance of work-life balance and
offer flexible working options to accommodate personal needs and
preferences. A supportive and collaborative work environment: We
foster a culture of teamwork, collaboration, and mutual respect, where
every team member is valued and supported in their professional and
personal growth. Closing We welcome applicants from all backgrounds,
irrespective of gender, nationality, religion, or any other personal
characteristic. Our organization values diversity and inclusion, and
we encourage individuals from all walks of life to apply for this
position. Even if you believe you may not meet all the listed
requirements, we encourage you to submit your application. We believe
that diverse perspectives enrich our team and contribute to our
collective success. Your unique skills, experiences, and perspectives
are highly valued, and we look forward to considering your
application.
- Qualifikation
- Arbeitskräfte
- Verdienst:
- n.a.
- Bewerbung an
- Rhesis AI GmbH
Am Strandkai 1
De 20457 Hamburg
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