- Collaborate with data scientists, software engineers, and stakeholders to understand business requirements and translate them into technical solutions using machine learning techniques.
- Develop machine learning models and algorithms, utilizing techniques such as supervised and unsupervised learning, deep learning, natural language processing, and computer vision.
- Clean, preprocess, and analyse large datasets to extract meaningful insights and features for model training.
- Evaluate and select appropriate modelling techniques and algorithms to address specific problems.
- Build scalable and efficient machine learning pipelines and workflows for data processing, feature engineering, model training, and deployment.
- Optimize and fine-tune machine learning models for performance and accuracy.
- Deploy machine learning models into production systems and monitor their performance in real-world applications.
- Collaborate with the DevOps team to ensure scalability, reliability, and efficiency of deployed models.
- Stay updated with the latest advancements and trends in machine learning and AI technologies.
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. A Ph.D. is a plus.
- 4+ proven experience working as a Machine Learning Engineer or in a similar role.
- Strong proficiency in programming languages such as Python, R, or Java. Proficiency in libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, etc.
- Solid understanding of machine learning algorithms, data structures, and statistical concepts.
- Experience in handling and processing large-scale datasets using SQL, NoSQL, or distributed computing technologies (Spark, Hadoop, etc.).
- Hands-on experience in building and deploying machine learning models in cloud environments (AWS, Azure, Google Cloud).
- Familiarity with software development practices, version control systems (Git), and agile methodologies.
- Excellent problem-solving skills, critical thinking, and ability to work in a dynamic and collaborative team environment.
- Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Experience with containerization technologies (Docker, Kubernetes).
- Knowledge of reinforcement learning techniques.
- Contributions to open-source machine learning projects or publications in related conferences/journals.
- Join an enthusiastic and diverse global team at GFR, where motivated individuals collaborate in a friendly environment.
- Embrace a culture of high performance and stellar ambition, where excellence is our standard at GFR.
- Continuous Growth and Career Development. From day one, you have the chance to contribute your ideas and create a meaningful impact. Our flat hierarchies and swift decision-making processes provide an open platform for your career progression.
- A strong management team with a proven track record in academia, business and technology: owning a worldwide patent and founding and exiting their previous startup and assisting with the subsequent IPO to learn from.
- Competitive compensation.
Machine Learning Engineer - Berlin, Deutschland - GFR
Beschreibung
ABOUT US
GFR is building the leading AI platform for accounting automation. Our mission is to help accounting firms and accounting professionals in large enterprises to be more productive. Our flagship product, GFR Accounting Autopilot, combines advanced mathematical models with a state-of-the-art infrastructure, equipped with proprietary AI/ML modules to help our clients grow their business despite a severe talent shortage and increasing legal complexity.
Our goal is to empower tax advisors and accountants to spend more time with their clients and on their clients' most important problems, and less time in the kafkaesque maze of traditional accounting systems and processes.
YOUR MISSION
We are seeking a highly skilled and motivated Machine Learning Engineer to join our GFR team. As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex business problems. You will work closely with cross-functional teams to understand requirements, collect and preprocess data, build models, and deploy them into production environments.
YOUR RESPONSABILITIES
Requirements
YOUR PROFILE
Preferred Qualifications:
Benefits
WHY US?
This is a hybrid role, based in Berlin (top location) with an expectance to ideally be on-site/in office for 2 days a week.