\nAbout Us\nDeep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.\n\n\nWhere You Fit In\nIn this role, you will be responsible for leveraging large-scale human genetic datasets (e.g., whole genome sequencing, whole exome sequencing, array genotyping) for genetic target identification and patient stratification. You will be responsible for the development and implementation of analyses methods. You will collaborate closely with machine learning scientists for the development of integrative approaches using artificial intelligence to detect and prioritize associations. You will work closely with the statistical genetics, bioinformatics and biology teams to prioritize targets. \nWe are looking for someone with a PhD in statistical genetics and 2+ years of postgraduate experience who is passionate about the potential of artificial intelligence to disrupt therapeutic target discovery and who is able to adapt to changing requirements in a rapidly evolving field. \n\n\n\nKey Responsibilities\n* Perform advanced  analyses, including GWAS, PheWAS, rare variant burden testing, Mendelian randomization. Apply and improve post-hoc analysis methods to investigate and prioritize potential targets.\n* Develop robust methods for integrating AI-powered variant effect predictors with traditional analysis techniques.\n* Create robust containerized software workflows and execute them at scale on Google Cloud Platform (GCP) infrastructure.\n* Participate in cross-functional projects to improve and apply genomic AI models for target discovery and patient stratification.\n* Translate findings into biological insights that inform drug target and patient prioritization.\n* Actively participate in code review and testing (your own and others from within the team).\n\n\n\nBasic Qualifications\n* PhD in human statistical genetics or related discipline with 2+ years of postgraduate experience and a robust publication record.\n* Experience with large-scale human genetic association analyses (WGS, WES, GWAS, PRS, etc.) using biobanks or other large datasets.\n* Strong scientific programming skills (Python strongly preferred) and experience with high-throughput or cloud compute (especially GCP).\n* Solid understanding of human genetics and basic understanding of human biology.\n* Critical thinking, intellectual curiosity and commitment to innovation. \n* Excellent communication and interpersonal skills.\n* Excellent documentation of workflows and results\n\n\n\nPreferred Qualifications\n* Post-graduate experience in either academia or industry.\n* Direct experience with UK Biobank. \n* Familiarity with variant effect predictors, and machine learning or AI models in the context of target discovery.\n* Familiarity with systems biology techniques and/or single-cell sequencing data. \n* Experience integrating over multi-modal data to derive insights with, for example, large language models.\n\n\n\nWhat we offer\n* A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery. \n* Highly competitive compensation, including meaningful stock ownership.\n* Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program. \n* Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.\n* Maternity and parental leave top-up coverage, as well as new parent paid time off. \n* Focus on learning and growth for all employees - learning and development budget & lunch and learns.\n* Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.\n\n\n\n\n\n\nDeep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.\n\n\nDeep Genomics thanks all applicants, however only those selected for an interview will be contacted. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Testing and Cloud jobs that are similar:\n\n $65,000 — $97,500/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nNorth America

\n\n\nAbout Us\nDeep Genomics aims to revolutionize drug development using artificial intelligence built to decode RNA biology and RNA therapeutics. Our proprietary AI platform enables us to decode the enormous complexity of RNA biology to find novel targets, mechanisms, and molecules that are not accessible through traditional methods. Founded in 2015, our multidisciplinary team includes expertise in a diverse range of disciplines including those found in a traditional drug company, as well as machine learning, statistical genetics, applied data science, deep bioinformatics, software engineering and laboratory automation. Deep Genomics is based in Toronto, Ontario and Cambridge, Massachusetts.\n\n\nOpportunity\nWe are looking for a Senior MLOps Engineer who can make our training and inference pipelines highly performant, scalable, and replicable. In this role, you will collaborate closely with our ML, data science, and software engineering teams to develop and design new systems from scratch as well as re-engineering our existing workflows and applications. You will also guide development of new infrastructure and processes.\nYou’ll have the opportunity to make real changes at our company. How do you believe Deep Genomics should consume genomic data, schedule training workloads, evaluate model performance, and make inference available to applications? We’d love to discuss it with you, and ultimately let you drive the direction.\n\n\nIdeal Candidate\nWe are looking for someone with 3+ years of experience who can adapt to changing requirements in a rapidly-evolving field, and who can also help their colleagues improve their skills and understanding.\n\n\n\nResponsibilities: \n* Package models, deploy to production environments, and monitor usage and performance.\n* Design, implement, and deploy ways to make complex deep learning models usable by biologists and other domain specialists.\n* Manage ML infrastructure, both on premises and in the cloud.\n* Rapidly prototype POCs in partnership with ML scientists and other stakeholders.\n* Test models at scale and ensure CI/CD best practices are followed by the whole team.\n\n\n\nNice to have:\n* Previous experience in a startup and/or taking projects from inception to production.\n* Experience with either biological or genomic data and applications.\n\n\n\nWhat we offer: \n* Building technologies that can directly impact the lives of patients.\n* A competitive salary plus equity compensation (ESOPs).\n* A wide array of company-paid benefits.\n* Flexibility in remote working.\n* Exceptional opportunities for learning and growth in a world-class team of researchers and software developers, working at the intersection of the most exciting areas of science and technology.\n\n\n\n\n\nDeep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.\n\n\nDeep Genomics thanks all applicants, however only those selected for an interview will be contacted. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Senior and Engineer jobs that are similar:\n\n $70,000 — $110,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nToronto, Ontario

\nAbout Us:\n\n\nDeep Genomics is a startup company that aims to revolutionize drug development by leveraging expertise in artificial intelligence (AI) and genome biology to decode RNA biology. Our proprietary platform, the AI Workbench, enables us to decode the enormous complexity of RNA biology to find novel targets, mechanisms, and molecules that are not accessible through traditional methods. We use this advanced technology to discover genetic targets for human diseases, and develop steric-blocking oligonucleotides (SBOs) that achieve expression increase for the treatment of genetic disease. Founded in 2015, our multidisciplinary team includes expertise in a diverse range of disciplines including those found in a traditional drug company, as well as genetics, machine learning, laboratory automation, and software engineering.  Deep Genomics is based in Toronto, Ontario with an additional location in Cambridge, Massachusetts.\n\n\nWhat You will Be Doing:\n\n\nAs a (Senior) Research Scientist of Statistical Genetics, you will be responsible for analyzing large-scale human genetic data-sets (e.g., whole genome sequencing, whole exome sequencing, array genotyping) to identify potential genetic targets for oligonucleotide therapeutics. You will lead these efforts by utilizing variant effect predictors on the genomic data, and refining or developing statistical techniques to nominate candidate genes. You will collaborate with machine learning scientists for the development and improvement of variant effect prediction models. You  will work closely with the statistical genetics and bioinformatics teams, and interface regularly with the target biology team. \n\n\n\nWhat you bring: \n* PhD in biostatistics, human statistical genetics, or related discipline.\n* Robust publication record.\n* Proven experience with large-scale human genetic data analysis.\n* Strong scientific programming skills (e.g., Python, R and Unix shell).\n* Solid understanding of human genetics and basic understanding of human biology.\n* Proven capacity to excel in a dynamic, fast-paced, innovative setting that prioritizes teamwork, collaboration, and communication both within the team and across the department, all while maintaining the utmost standards of scientific rigor and integrity.\n* Critical thinking, intellectual curiosity and commitment to innovation. \n* Excellent communication and interpersonal skills.  \n\n\n\nNice to have: \n* Post-graduate experience in either academia or industry.\n* Familiarity with high-performance computing environments (Google Cloud, AWS, Azure etc.) and databases.\n* Direct experience with UK Biobank or other large-scale genomic data.\n* Familiarity with variant effect predictors, and machine learning or AI models in the context of target discovery.\n\n\n\nWhat we offer:\n* A highly competitive salary and meaningful equity compensation (ESOPs).\n* A wide array of company-paid benefits.\n* Opportunities for remote, hybrid or in-person work at our Toronto and Boston offices.\n* Exceptional opportunities for learning and growth.\n* A bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology.\n\n\n\n\n\nDeep Genomics thanks all applicants, however only those selected for an interview will be contacted.    \n\n\nDeep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Excel and Excel jobs that are similar:\n\n $30,000 — $60,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nToronto, Ontario

\nAbout Us\nDeep Genomics is a startup company that aims to revolutionize drug development by leveraging expertise in artificial intelligence (AI) to decode RNA biology. Our proprietary platform, the AI Workbench, enables us to decode the enormous complexity of RNA biology to find novel targets, mechanisms, and molecules that are not accessible through traditional methods. We use this advanced technology to develop steric-blocking oligonucleotides (SBOs) that achieve expression increase for the treatment of genetic disease. Founded in 2015, our multidisciplinary team includes expertise in a diverse range of disciplines including those found in a traditional drug company, as well as machine learning, laboratory automation, and software engineering.  Deep Genomics is based in Toronto, Ontario with an additional location in Cambridge, Massachusetts. \n\n\nWhere You Fit In \nWe are looking for a Senior Data Scientist to join our team of machine learning scientists, software engineers, and wet lab biologists. Your role will focus on collaborating closely with bench scientists to design experiments and analyze data. You will also work alongside machine learning scientists, applying ML models to practical, impactful projects. \n\n\n\n\n\nWhat you will do:\n* Collaborate with wet lab scientists on experimental design and data analysis.\n* Develop and maintain tools for automating data analysis pipelines.\n* Benchmark internal and external machine learning models, focusing on applications like variant effect prediction and RNA therapeutic design.\n* Mentor and guide junior data scientists, fostering a supportive and collaborative environment for team growth and learning.\n\n\n\nWhat you bring:\n* An MSc or PhD in computational biology, biostatistics, or a related field.\n* At least three years of experience working with experimental teams.\n* A strong understanding of statistics.\n* Solid experience in software engineering best practices, such as version control, unit testing, and continuous integration.\n\n\n\nNice to have:\n* Experience with deep learning models applied to biology\n\n\n\nWhat we offer:\n* A highly competitive salary and meaningful equity compensation (ESOPs)\n* A wide array of company-paid benefits\n* Exceptional opportunities for learning and growth working alongside a world-class team of researchers and software developers working at the intersection of the most exciting areas of science and technology.\n\n\n\n\n\nDeep Genomics thanks all applicants, however only those selected for an interview will be contacted.    \n\n\nDeep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design and Senior jobs that are similar:\n\n $47,500 — $85,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nToronto, Ontario