Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Co-Op, Structuring Scientific Data for Discovery
Cambridge, MA USA; San Francisco, CA USA
Actively hiring, first seen by us 6 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- New graduates
- For current students
Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering
What you’ll work on
Full postingFine-tune and evaluate models for scientific data extraction
Build retrieval and RAG pipelines for documents, tables and figures
Generate and validate structured datasets from literature and patents
Run end-to-end pipelines and analyze results against evaluation criteria
Document findings and present them to the team
From the employer’s posting
Fine-tune and evaluate language, multimodal, or specialized models for scientific data extraction
Build retrieval and RAG pipelines surfacing relevant documents, tables, and figures
Generate and validate structured datasets extracted from scientific literature and patents
Run end-to-end pipelines and analyze results against clear evaluation criteria
Document findings and present them to the team
Education & alternatives
What You'll Need to Succeed - Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering - Solid foundation in machine learning fundamentals and Python
About Lila Sciences
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 28, 20266 days ago
- Recorded sightings
- 8
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 6
Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Lila Sciences is hiring
16 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is steady
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
Where the posting names them
- Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering - Solid foundation in machine learning fundamentals and Python - Familiarity with NLP or computer vision concepts
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Your Impact at LILA
Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. Our team turns unstructured scientific knowledge, including literature, patents, and technical reports, into structured signals that power downstream Lila applications.
As a Data Extraction Co-Op, you will work alongside research scientists and engineers on a focused sub-problem in this stack. You will fine-tune and evaluate models for scientific knowledge extraction and retrieval, build pipelines for messy real-world data, and ship work that flows into production systems.
What You'll Be Building
- Fine-tune and evaluate language, multimodal, or specialized models for scientific data extraction
- Build retrieval and RAG pipelines surfacing relevant documents, tables, and figures
- Generate and validate structured datasets extracted from scientific literature and patents
- Run end-to-end pipelines and analyze results against clear evaluation criteria
- Document findings and present them to the team
- Contribute to a publication or open-source project where the work supports it
What You'll Need to Succeed
- Pursuing a Bachelor's, Master's, or PhD in CS, chemistry, materials science, physics, biology, or chemical engineering
- Solid foundation in machine learning fundamentals and Python
- Familiarity with NLP or computer vision concepts
- Curiosity about scientific data and willingness to learn quickly in a research setting
- Clear written and verbal communication
Bonus Points For
- Coursework or projects involving multimodal models or document understanding (OCR, table and figure extraction)
- Experience with LLM applications, embeddings, or retrieval systems (chunking, reranking, vector search)
- Experience building evaluation sets or annotation workflows
- Experience working with messy real-world data
- Interest in scientific document parsing
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Cambridge, MA USA; San Francisco, CA USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
We’re All In Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.