Senior Machine Learning Engineer - NLP

Senior Machine Learning Engineer - NLP

This job is no longer open
ScienceIO is a Series A startup building a state-of-the-art NLP platform that can detect and extract over 9 million healthcare concepts, clinical variables, and medical codes in text. We capture a broad spectrum of information, spanning medical conditions, devices, procedures, vitals, biomarkers, mutations, and more — in a single line of code. Our mission is to use this technology to build a more transparent, connected, and equitable healthcare system. 

Learn more about us on Not Boring ( and TechCrunch ( Also, check out the press release about our participation in Mayo Clinic's Accelerator program: (

As a Senior Machine Learning Engineer, you’ll be focusing on our ML platform and optimization of NLP transformer models critical to our business. This is a great opportunity to help build an end-to-end ML lifecycle environment, providing secure, HIPAA compliant development infrastructure for data scientists, as well as deployment of both real-time and batch prediction for confidential medical documents.

The role & opportunity

    • Be responsible for developing and maintaining a holistic cloud platform to manage our ML development services and deployment pipelines
    • Take ownership of ML projects: optimize research-grade models developed by data scientists, manage fine-tuning, deployment.
    • Take ownership of end-to-end predictive modeling projects which include data processing and training machine learning models. Also, Develop best practices and guidance around setting up data processes to support varying degrees of operational and analytical needs
    • Coach and mentor engineers and other peers on ML best practices, DevOps culture, etc.
    • Work with partner teams to ensure good data security and governance in an analytical environment
    • Ensure and monitor the reliability of deployed models in terms of scalability, latency, and ability to rollback releases
    • Develop governance and monitor models for performance

Who you are

    • Have 3+ years of relevant experience in ML engineering, implementing training environments, deployment pipelines, or related software engineering
    • Are experienced in solution architecting compute environments, batched orchestration, and other data platform components.
    • Have expertise with distributed computational platforms
    • Comfortable with and understand differences and trade-offs between various database systems and data formats: SQL, NoSQL, BigQuery, Parquet, JSON, etc.
    • Familiar with ML platforms: Kubeflow, MLFlow, Vertex AI, Sagemaker, ZenML
    • Embrace a generative culture and excel in rapidly changing/evolving environments
    • Have a bachelor’s degree with a focus on computational science (CS, Physics, Bioinformatics) or equivalent experience

Technologies we’d like you to use day-to-day:

    • Python, Git, Docker, PyTorch, AWS, GCP, Sagemaker, AWS Batch, Dask and more
We are a learning organization and are happy to train on things that you’re less familiar with as long as the core expertise is there. If you feel like you don't meet all requirements for this role, we encourage you to apply anyways. We know the confidence gap and imposter syndrome get in the way of meeting incredible candidates and don't want it to go get in the way of meeting you.

More about ScienceIO

Each year, more than two trillion gigabytes of data are created by our healthcare system. Most healthcare data is incredibly tough to work with — key insights are hidden away in notes, forms, faxes, and PDFs. But if we can understand the data, we can understand how to care for patients better, find individuals with unmet needs, lower the cost of care, and improve human health.
ScienceIO is on a mission to transform how we work with healthcare data to build a more transparent, connected, and equitable healthcare system.

Our AI platform is purpose-built to decode the language of medicine and unlock the full potential of healthcare data. Our real-time APIs transform messy unstructured data to create insights, streamline healthcare operations, and provide the building blocks for new patient solutions.

ScienceIO is backed by top-tier investors (including Section 32, Lachy Groom, Quiet Capital, and more). Our team has experts in machine learning, medicine, biology, and healthcare operations. We’re a deeply curious, caring, and collaborative team passionate about improving the lives of patients.

Learn more about us on Not Boring ( and TechCrunch (

What’s it like to work at ScienceIO?

At ScienceIO, we measure success by how well we empower our users. We love when people lift up the best ideas from anywhere in the team and gather support behind them. We care deeply about continuous learning and cultivating empathy within our team and with our users. The members of our team, regardless of their role or seniority, feel they can trust and learn from one another.
Our team believes differences should be celebrated and are committed to building a diverse and inclusive team and culture. We welcome different perspectives and opinions to foster innovation, authenticity, and excellence across all parts of our company and are committed to providing employees with a work environment free of discrimination and harassment.

As an Equal Opportunity Employer, ScienceIO highly encourages applicants from all walks of life. All employment decisions at ScienceIO are based on business needs, job requirements, and individual qualifications without regard to an actual or perceived race, color, sex, pregnancy, sexual orientation, gender identity or expression, age, national origin, political affiliation or belief, religion, disability, uniformed service, marital status or any other status protected by law.


• Unlimited PTO
• Health, vision, and dental insurance
• 401(k) plan with all fees covered
• Up to 16 weeks of flexible, paid parental leave for all employees, in case of birth, adoption, or other covered events
• Life insurance and short & long term disability insurance
• Public transportation subsidy covering subway/train, biking, rideshare, or other valid transportation programs for commuters
• Stipends for home office supplies and for books & professional development
• A flexible-first workplace, with the freedom to work in our beautiful offices or remotely as needed based on the needs of your role, team, and the business
• The opportunity to grow alongside a company shaking up an old-school industry, including training, mentorship, and coaching from leadership
• An inclusive and thoughtful community committed to the mission of improving healthcare
This job is no longer open
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