Machine Learning Engineer Pytorch/ TensorFlow/ AWS

Job descriptions
We are seeking a machine learning engineer to strengthen our expertise in machine learning and deep learning model development. As a machine learning engineer in our team at Gene Solutions, you will be working in a dynamic, multidisciplinary and fast-paced research-oriented environment. You will collaborate closely with data scientists, machine learning engineers, biologists and immunologists to design, develop, implement new machine learning models and optimize existing models, to accelerate our early cancer detection projects. You will contribute to multiple research projects, requiring not only a strong data management capability, but also excellent personal planning skills. If you are passionate about machine learning and eager to apply your expertise in genomic data science research, we strongly encourage you to apply and join our team.

Key Responsibilities
• Develop advanced machine learning, deep learning models which focus on early cancer detection.
• Evaluate, tailor and fine-tune existing pre-trained models to address our research question.
• Maintain and improve existing machine learning, deep learning models developed in-house.
• Work with large and complex genomic datasets.
• Be an active member of an interdisciplinary team. Collaborate closely with other data scientists and bioinformaticians to develop and implement an end-to-end model cycle: feature design, data pre-processing, data clean-up, feature selection and model development.
• Responsible for end-to-end model deployment in production.
• Keep up to date with the latest advances in machine learning, deep learning, specializing in early cancer detection problems.

Required qualifications
• A master's degree in computer science, information technology, mathematics, computational biology, bioinformatics or related field with at least 1 year of experience, or equivalently, a bachelor's degree with +3 years of working experience. Ph.D. is a plus.
• Solid knowledge in theoretical machine learning and deep learning.
• Solid knowledge in algorithms and data structure.
• Hands-on experience with proven track record of machine learning, deep learning model implementation in Pytorch or TensorFlow. Strong proficiency in python and BASH scripting. Knowledge of R is a plus.
• Hands-on experience working with Linux system, high-performance computing clusters (HPC), containerization, e.g. docker, singularity.
• Good understanding of common statistical methods, e.g. hypothesis testing, cross-validation, statistical feature selection method.
• Excellent verbal and written communication skills to present bioinformatics data analysis findings with effective data visualizations in weekly multidisciplinary team meeting.
• Nice to have: experience with cloud-based platforms (AWS).
• Nice to have: experience with MLOps frameworks.
• Nice to have: experience with GitHub/GitLab in collaboration.
• Strong motivation, self-driven and curiosity to learn.

• 13th month salary.
• Holidays and full annual leave in accordance with State regulations.
• Participate in all insurances (social insurance, health insurance, unemployment insurance), enjoy full policies and regimes according to the Labor Law.
• Dynamic and humane working environment Annual trip.