Careers

Pixel Scientia Labs is an impact-driven machine learning consulting firm. We fight cancer, climate change, and other global challenges by creating algorithms to turn images into insights.

We recognize that the most impactful projects are not done alone but are tackled by interdisciplinary teams. Our goal is to strengthen the machine learning component -- often pushing beyond the limits of current technology to solve new problems.

We work with clients who are using pathology or remote sensing imagery and guide them (through advisory or collaborative relationships) to select and implement better models that can generate much needed insights.

Are you tired of the bureaucracy of larger organizations but seek a better work-life balance than the intense environment of a startup? Does the opportunity to contribute to multiple projects simultaneously excite you?

Logistics:

  • Work from anywhere in the US (eastern time zone preferred)
  • Flexible schedule (aside from regularly scheduled meetings with Pixel Scientia team and clients)

Computer Vision Engineer - Computational Pathology (Remote)

In this role, you will be working directly with the founder of Pixel Scientia Labs on projects that can make a difference. Continually building your skill set to meet new challenges is expected. We value the work that we do but also time with our families.

We are looking to hire a curious and intrinsically-driven Computer Vision/Machine Learning Engineer to help support a variety of client projects in pathology. Your focus will be on planning, implementing, and validating new models that tackle challenges in image analysis for precision medicine.

Responsibilities:

  • Creating computational pathology solutions to improve pathologists’ workflow, biomarkers, diagnostics, prognostics, treatment response, etc.
  • Implementing state-of-the-art techniques from recent research publications
  • Comparing and contrasting different algorithms or tools
  • Analyzing model performance to identify failure modes and suggest next steps
  • Working with Pixel Scientia team members and client's team to plan, develop, train, test, and deliver a successful project
  • Clearly documenting model functionality, results, limitations, project progress, etc.
  • Continually building your skill set by educating yourself on topics needed for project delivery

Requirements:

  • Masters in Computer Science, Data Science, Software Engineering, or related field
  • 2-5 years’ experience implementing machine learning, computer vision, and deep learning solutions
  • Experience developing, training, and validating both traditional machine learning and deep learning models
  • Experience implementing algorithms from research papers
  • Proficiency in Python, Tensorflow/Keras or PyTorch, sklearn
  • Practical and theoretical understanding of machine learning/computer vision
  • Ability to work independently as well as collaboratively with a diverse team of engineers and scientists
  • Experience with version control such as Git
  • Highly motivated and organized
  • Problem solver who can grind on hard problems and present novel solutions to obstacles
  • Willing to learn new skills and adapt to fluctuating workloads
  • Authorized to work in the United States

Nice-to-haves:

  • Experience with Docker containers and cloud-based computing environments
  • Experience deploying and maintaining machine learning models
  • Experience supporting publications in scientific journals/conferences

Apply now

Computer Vision Researcher - Computational Pathology (Remote)

In this role, you will be working directly with the founder of Pixel Scientia Labs on projects that can make a difference. Continually building your skill set to meet new challenges is expected. We value the work that we do but also time with our families.

We are looking to hire a curious and intrinsically-driven Computer Vision/Machine Learning Researcher to help support a variety of client projects in pathology. Your focus will be on researching, planning, implementing, and validating new models that tackle challenges in image analysis for precision medicine.

Responsibilities:

  • Creating computational pathology solutions to improve pathologists’ workflow, biomarkers, diagnostics, prognostics, treatment response, etc.
  • Working with Pixel Scientia team members and client teams to research, plan, develop, train, test, and deliver a successful project
  • Reviewing literature and presenting report or experimental findings
  • Identifying and adapting state-of-the-art models to exploit new capabilities
  • Guiding Machine Learning Engineers in implementing algorithms
  • Comparing and contrasting different algorithms
  • Analyzing model performance to identify failure modes and suggest next steps
  • Clearly documenting model functionality, results, limitations, project progress, etc.
  • Writing a 500-1000 word blog article each quarter on a topic of interest to those using machine learning in pathology
  • Keeping up with the state-of-the-art in machine learning and computer vision, especially as it relates to pathology images
  • Continually building your skill set by educating yourself on topics needed for project delivery

Requirements:

  • PhD in Computer Science, Data Science, or related field
  • 2-4 years’ experience implementing machine learning, computer vision, and deep learning solutions
  • Record of scientific publications in high impact technical journals/conferences
  • Experience developing, training, and validating both traditional machine learning and deep learning models
  • Proficiency in Python, Tensorflow/Keras or PyTorch, sklearn
  • Practical and theoretical understanding of machine learning/computer vision and research principles, and awareness of state of the art techniques
  • Able to explore a topic, develop a research plan, and execute on that plan
  • Ability to work independently as well as collaboratively with a diverse team of engineers and scientists
  • Effective communicator of technical topics to a less technical audience, verbally and through articles, blogs, etc.
  • Broad knowledge of computer vision/machine learning and its application to pathology
  • Experience with version control such as Git
  • Highly motivated and organized
  • Problem solver who can grind on hard problems and present novel solutions to obstacles
  • Willing to learn new skills and adapt to fluctuating workloads
  • Authorized to work in the United States

Nice-to-haves:

  • Experience working in cloud-based computing environments
  • Experience with topological features, graph convolutional networks, sequence models, generative adversarial networks, deep learning interpretability methods

Apply now