Machine Learning Engineer - NLP


Remote in North America
Job Function
Toronto | Development | Intermediate

We are seeking a Machine Learning Engineer – NLP to join our growing R&D team! You will work on complex and challenging NLP problems that will have an impact on the 41,000+ scientists across the world who rely on BenchSci for their research. Reporting to the Engineering Manager, R&D, you’ll apply your domain expertise to build advanced machine learning algorithms, collaborate with data engineers to build benchmarking and data preparation pipelines, and work with core infrastructure engineers to deploy and monitor your models in our production system. In this role, you will have the opportunity to apply state-of-the-art solutions that will shape the future of scientific discovery. 

You will:

– Build innovative ML models that enhance the speed and quality of life-saving research

– Collaborate with data and core infrastructure engineers to solve the complex problems of extracting insights from biomedical text data

– Continuously improve our machine learning workflow by keeping up to date with the latest PyTorch optimizations and expanding our usage of modern tools such as DVC

– Own the solutions and long-term technical investments that will drive innovation at BenchSci

– Work with BenchSci’s R&D scientists and Chief Science Officer to learn, model, and capture the nuances of biology

– Be empowered to own your solutions

– Participate in sprint planning, estimation, and design/code reviews

– Work with on-site PhD scientists that give immediate feedback on models

– Work with fresh datasets that are custom curated and constantly updated 

– Receive one-on-one coaching and investment in your personal and professional growth

You have:

– 3+ years of experience working as a professional developer or researcher applying machine learning techniques to solve business problems

– Strong experience with Python and programming fundamentals

– Extensive experience with NLP and PyTorch

– Experience with data manipulation and processing using SQL or pandas 

– A growth mindset and a constant desire to learn

– Strong cross-team communication and collaboration skills

– Experience recreating and applying state-of-the-art NLP research

Nice to haves, but not mandatory qualifications:

– A background in Life Science

– Working knowledge of data versioning tools such as DVC for machine learning

– Working knowledge of distributed systems and data processing fundamentals

– Knowledge of distributed data processing abstractions like Beam or Spark

– Working knowledge of machine learning data fundamentals such as data splits, training-serving skew, common data representations such as embeddings or multi-hot encodings, sampling strategies for active learning

– Working knowledge of how to evaluate classification model quality, such as precision, recall, F1, PR/ROC curves

Apply Now

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