Senior Machine Learning Scientist

The company Elucidata is a TechBio Company headquartered in San Francisco, with a mission to make life sciences data AI-ready. Elucidata's platform Polly, powered by LLM, assists research teams in managing and analyzing large volumes of biomedical data. The company is pioneering GenAI in life sciences R&D with leading BioPharma companies such as Pfizer, Janssen, NextGen Jane, and more. Elucidata was recognized as the "Most Innovative Biotech Company, 2024", by Fast Company and has a team of 120+ experts across the US and India. In September 2022, they raised $16 million in their Series A round led by Eight Roads, F-Prime, Hyperplane, and IvyCap. As a Senior Machine Learning Scientist at Elucidata, you will be responsible for developing advanced ML solutions to analyze complex biological datasets. This role presents an exciting opportunity to work at the intersection of machine learning and life sciences, enabling transformative insights from multi-omics and biomedical data. Your key responsibilities will include designing, implementing, and optimizing machine learning algorithms for analyzing biological data. You will also develop approaches to integrate diverse data types to derive meaningful biological insights. Staying updated with state-of-the-art ML methods and collaborating with bioinformaticians, data scientists, and domain experts will be essential to ensure seamless integration of ML models into workflows. Additionally, you will optimize and deploy ML models on cloud platforms for scalable analysis and collaborate on preprocessing, feature engineering, and quality control of large biological datasets. Qualifications for this role include a Masters or Bachelors degree with 3-4 years of experience in Machine Learning, Computer Science, Bioinformatics, Computational Biology, or a related field. You should have a solid understanding of machine learning algorithms and statistical methods, proficiency in Python and ML frameworks, strong problem-solving skills, and excellent communication and interpersonal skills. Experience with cloud technologies and scalable computing platforms would be beneficial. Desirable qualifications include experience with biological datasets and applying ML to multi-omics data integration, familiarity with cloud technologies, biomedical ontologies, pathway analysis, or systems biology approaches, and a strong publication record in ML or bioinformatics journals.,