September 16, 2022 Job ID: 21213

AbCellera is a young, energetic, and rapidly growing biotech company with an amazing team that searches, decodes, and analyzes natural immune systems to find antibodies that its partners can develop into drugs to prevent and treat disease.

We are seeking a highly-motivated and experienced Data Engineer to join our Machine Learning team. We believe that we can tackle the most challenging scientific problems through teamwork, innovation, and mutual support. If you’re a self-motivated and creative problem solver who thrives in a fast-paced, collaborative environment, we’d love to hear from you.

How you might spend your days:

  • Wrangling both structured and unstructured data
  • Organizing and joining data sets from disjoint data storage systems
  • Doing exploratory data analysis on imaging, sequence, and wet bench experimental data sets
  • Implementing automated, repeatable, testable pipelines that join together and process diverse data sets
  • Designing metrics to measure data set characteristics and quality
  • Discovering data characteristics that influence ML model inference accuracy, and ways to mitigate problems
  • Cleverly repurposing or augmenting existing internal and external tools to build manual data labeling workflows, and orchestrating data labeling efforts
  • Auditing data access for compliance with data governance policies
  • Providing valuable insights into platform and data pipelines development and deployment
  • Participating in code reviews with the machine learning team and broader data science group

We'd love to hear from you if you have:

  • A team-first attitude and thirst to learn and improve in machine learning, software engineering, data science, and the life sciences!
  • B.S. in computer science, data science, machine learning, or similar
  • 2+ years of experience working with machine learning data sets using Python, Pandas, and SQL, at the level of querying and joining together data sets
  • Excellent organizational skills and attention to detail
  • Enthusiasm for cross-team collaborative work, especially across life science disciplines

In addition, the ideal candidate will have:

  • Experience in the life sciences, including imaging and bioinformatics
  • Experience with other components of our opinionated ML stack, including PyTorch, Plotly / Dash, Parquet, DVC, and Dask
  • Experience with our infrastructure stack, including AWS (S3, IAM, CloudWatch, Route53, RedShift), Terraform, Kubernetes, Docker, bazel

Offers & benefits:

  • The opportunity to work with an inspired team on challenging problems that matter
  • An attractive compensation package, including health and lifestyle benefits
  • A minimum of 3 weeks’ vacation
  • Opportunities for personal and professional development

About AbCellera: 

At AbCellera, we’re solving tough problems and creating innovative solutions from the ground up - custom immunizations, microfluidics, high-throughput imaging, genomics, computation, machine learning and laboratory automation. We’re revolutionizing how our scientists can explore antibodies and the scale at which they can do so. This is life-changing research and you could be a part of it.

You’ll join a diverse and multi-disciplinary team of biologists, biochemists, engineers, bioinformaticians, computer scientists and physicists - all working together to bring better therapies to patients. We’re a growing company with a high-throughput pipeline and the drive to be the best in the industry. This isn’t just about having the best technology. We know we need a world-class team of visionaries and innovators. We look for people with drive and energy. Idealists. People we love and people we trust. This may be unconventional, but it is the key to our success. We’re looking for someone like you to help us get there.

To apply: 

Please send us your application through our website and refer to Job ID 21213 in your cover letter. We apologize in advance, but we receive a large volume of applications, and will only contact those who are selected for an interview.

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