Mid-level Machine Learning Engineer, Bioinformatics

Deeplab combines superior software technologies with top-notch machine learning and data science research to offer services and products that tackle challenging real-world issues. This is an opportunity to join a dynamic, fast-paced ML/AI organization dedicated to research, innovation, and excellence. The culture at Deeplab bridges the gap between academic rigor and entrepreneurial agility. We promote an environment where the methodical, research-driven pursuit of knowledge meets innovative, quick decision-making. This synergy bolsters our pursuit of excellence and innovation in solving practical real-life problems. The Team We are currently expanding our ML team for bioinformatics solutions. This is part of an international research and development collaboration with industry partners in the general areas of drug discovery and cancer research. Our team takes on disruptive projects from ideation to productization, combining innovative ML concepts with cutting-edge production technologies. If you join, you'll be part of an interdisciplinary team that includes passionate ML engineers with backgrounds in both research and software development. The role We are seeking exceptional mid-level machine learning engineers who share our passion for solving challenging diverse bioinformatics industrial/research problems. You will have the chance to contribute to the creation of new R&D while utilizing cutting-edge machine learning across challenging projects with top-level academic/industrial partners. You'll also find fantastic opportunities for further development alongside the team. Mid-level Machine Learning Engineer candidates are expected to have experience in machine learning, either from prior practical experience in a relevant industry/research role, or demonstrated by their exceptional academic achievements in a related postgraduate degree. Requirements Candidates are expected to have a bachelor's or master's degree in Electrical & Comp. Eng., Machine Learning, or CS, and experience implementing and benchmarking machine learning algorithms for real-world data. They should also have 2+ years of hands-on industrial or academic experience with machine learning projects, proven research experience employing machine learning, knowledge of development processes using Linux, Git, Docker, etc. They must be proficient in Python, with experience in developing, testing, and maintaining production-grade machine learning applications using frameworks such as TensorFlow or PyTorch. It would be beneficial if candidates have familiarity with concepts in bioinformatics, computational biology, drug discovery, cheminformatics, and molecular biology. It would be an added bonus if the candidate is familiar with chemical informatics libraries and tools such as RDKit or Open Babel, and if they have an understanding of molecular modeling, docking simulations, or other computational techniques relevant to drug design. Candidates should also have experience with large scale cluster computing for machine learning modeling and the ability to build strong relationships in a challenging international environment. Great written and oral communication skills are crucial, along with the ability to present complex analyses in a clear, concise, and actionable manner. Responsibilities Your responsibilities will include developing machine learning algorithms and infrastructure, writing production-grade ML code, performing experimentation and benchmarking, statistical modeling and data analytics, and applying deep learning techniques to bioinformatics. You will also manage, curate, and preprocess diverse biological datasets to ensure quality and consistency for downstream machine learning tasks and ensure algorithms and models are optimized for both computational efficiency and scalability to handle large-scale biological datasets. Besides this, you must stay updated with the latest advancements in machine learning methodologies such as transfer learning, semi-supervised learning, etc, as well as bioinformatics and computational biology. Collaborating with cross-functional international teams is crucial. Benefits Benefits include supplementary private health insurance, flexible working hours, and remote work. You'll be working in high-end AI-tech and having an impact on real-world applications. There's a budget for home office equipment to ensure a productive workspace, personal growth opportunities, a visually pleasing and upbeat working environment at our new offices, and competitive salary depending on qualifications, expertise, and experience. Deeplab: An equal opportunity employer At Deeplab, we value diversity in terms of experience, knowledge, backgrounds, and perspectives. We provide equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition, and any other basis protected by law. We welcome those with disabilities or additional needs and will make accommodations as required. About the company Deeplab is a ground-breaking company that provides cutting-edge artificial intelligence R&D solutions to tough real-life problems. At DeepLab, we strive to bridge the gap between research and the industry: we aim to advance scientific breakthroughs while simultaneously incorporating research solutions in large-scale industrial and research projects. We nurture and fund academic-industrial synergies to explore new research directions and applications. Our vision encompasses the end-to-end interdisciplinary development and exploitation of ML research, providing solutions to key real-life problems. This effects real societal impact in both research and business communities. We have built solid partnerships with world-leading pharmaceutical companies in the area of drug discovery. We have been working in the field of bioinformatics, garnering a strong partnership with Taboola for the past 5 years. Together, we have introduced, co-developed and are responsible for the deep learning technology behind large-scale production pipelines related to personalization and recommendation, with impressive results to date. The system serves billions of recommendations daily to a user base of 1.4B unique users. You can find more information about us at deeplab.ai.