Senior Machine Learning Engineer

Full-timeNYC or RemoteTechnologyNYC or Remote

Overview

ScienceIO (now Veradigm Bedrock) is on a mission to make healthcare more transparent, connected, and equitable with the help of artificial intelligence. Since 2019, we've been developing language models optimized for responsible and secure use in healthcare.

Recently, we've been acquired by Veradigm, connecting our LLM training platform to a comprehensive network of over 400,000 providers and over 200 million patients while ensuring data integrity and protection of patient privacy.

As a Senior Machine Learning Engineer, you’ll focus on designing, training, and deploying custom generative LLMs aligned for responsible use in healthcare workflows on our proprietary datasets.

You'll be a part of a dedicated and curious team of experts in machine learning, medicine, biology, and healthcare workflows. We care deeply about making our healthcare system better for every patient and provider. Learn more about us from our Substack and our recent feature in Microsoft’s Technology Record.
  • The role & opportunity

    • You will be instrumental in building on this success and exploring new frontiers in healthcare ML. 
    • Concretely, you’ll participate in our paradigm shift to applying RL and alignment techniques to align generative models in biomedical/healthcare tasks. 
    • As a pivotal member of our team, you will contribute to multiple phases across the entire ML project lifecycle:
    • Conceptualizing generative models.
    • Building training and test data sets, and AI feedback models.
    • Deploying production models for use in real-time and batch APIs and chat interfaces.
    • You’ll create red team datasets and AI feedback models in the biomedical/healthcare domain using prompt engineering.
    • You’ll participate in engineering user experiences (backend, UX) which lower the bar for entry to contribute to model development.
    • You’ll develop and communicate ML engineering best practices with peers.
    • You will have the opportunity to focus on certain parts of the lifecycle that align with your interests and strengths as systems gain maturity.
  • Who you are

    • You have 5+ years of relevant experience in ML engineering, implementing state-of-the-art models, or related software engineering
    • You have a degree with a focus on computational science (CS, Physics, Bioinformatics) or equivalent experience
    • You have a strong interest and/or experience in Deep Reinforcement Learning (RL)
    • You have experience with distributed computational platforms and a firm understanding of the underlying concepts
    • You understand differences and trade-offs between various database systems and data formats: SQL, NoSQL, BigQuery, Parquet, JSON, etc.
    • You are familiar with ML platforms like Sagemaker, MLFlow, Vertex AI, ZenML, or Kubeflow
    • You are familiar with prompt engineering, parameter-efficient fine-tuning, and alignment of generative language models
    • You embrace a inclusive learning culture and excel in rapidly changing/evolving environments
  • Technologies we’d like you to use day-to-day:

    • Python, PyTorch, Hugging face
    • Git, Docker
    • AWS, GCP, Firebase, Dask, and more
  • Salary & Benefits

    • Salary range: $216,500 - $252,600
    • 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 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
We’re a close-knit team that prioritizes learning and growth, so we’re happy to train folks up on aspects they’re less familiar with as long as they have core expertise to accelerate our mission on day one. If you feel like you don't meet all the requirements for this role, we encourage you to apply anyway so we can get the chance to know you.

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.

In accordance with New York City Local Law 32, the expected salary for this role is between $216,500 and $252,600, plus a comprehensive benefits package as described above. This role may be eligible for additional compensation in the form of bonuses and/or stock options as well. All offers to candidates will ultimately be based on that candidate's individual experience and skillset, and not every candidate will qualify for the top end of the salary range.