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Research Engineer

Datalab, New York Office

Posted pay

$275K–$325K

a year

Location: New York Office
Work type: Onsite
Level: Not given
Experience: 3+ years
Skills in the job text: Python
PyTorch
Posted: Jul 6, 2026
Last check: 8 h ago
Job type: Research, Inference & ML systems, ML / AI engineering

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Datalab

About Datalab: funding, hiring and pay

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The role

We're looking for a Research Engineer to own problems end to end across our models, inference service, and product. You won't just train a model and hand it off. You'll take it from training through benchmarking, into our inference stack, and work with the team to integrate it into our products.

We're a small team that has shipped the current state of the art OCR model, Chandra. Our models collectively have 70k+ Github stars. Our tools are used internally at frontier AI labs like Anthropic, and Fortune 500 enterprises like Siemens.

Our team focuses on training small, efficient models that outperform much larger LLMs on domain-specific tasks (like OCR, structured extraction, tables). We move fast, prioritize practical results, and build tools that are open, reproducible, and built to last. You'll test hypotheses quickly, iterate on results, and balance experimental rigor with shipping to customers.

What you need

You've shipped models that made it into production. You understand how to balance exploration with delivery, and how to turn research insights into products people actually use.

3+ years experience training, fine-tuning, and evaluating deep learning models
Trained at least one production-grade model or system used in real-world applications
Deep expertise in PyTorch and Python, with strong fundamentals in deep learning (optimization, evaluation, architecture design)
Comfortable with data engineering, benchmarking, and performance profiling across hardware setups
Comfortable with an early stage startup – balance running ablations/benchmarks with shipping velocity

Nice to have

Have experience with OCR, document AI, or structured extraction
Have published work, whether that's a paper, a benchmark report, or a deep technical blog post
Have been a major contributor to open-source projects, especially in ML, vision, or NLP
Enjoy writing about your work and sharing learnings with the community

Day to day

A typical project might look like: identify a gap in extraction quality on long documents, train and benchmark a new model, optimize it for inference, and work with the team to ship it to users. Concretely:

Train and evaluate models: Train task-specific models (OCR, layout, text recognition, extraction). Explore architectures and training strategies to optimize task performance. This includes our open source models, like Marker, Surya, and Chandra.
Optimize inference: Profile and accelerate model inference across different hardware setups (H100s, B200s, L40s, CPUs).
Ship to product: Work with the team to integrate models into our API and product, helping define how new capabilities surface for end users. You will be involved from model training through integration, although your work will be weighted much more towards the model side than the product side.
Create and maintain datasets: Source, design, and clean datasets for supervised and synthetic training; create reproducible pipelines for data versioning and evaluation.
Experiment and benchmark: Run ablations, track metrics, and publish findings that inform model design and internal research direction.
Engage with users and partners: Occasionally join calls or Slack threads to better understand customer needs and inform your work.

Interview process

A 30-minute video call to evaluate fit
90-minute live architecture discussion
Culture fit interview/team meeting

At this stage of the company, every interview is somewhat custom, so these phases may be rearranged slightly.

About Datalab

Datalab is an applied research lab in New York. We train our own models to turn documents into data you can verify: scans, dense tables, handwriting, the pages other tools quietly get wrong.

Because we own the models, a customer's hard problem becomes a roadmap conversation, not a feature request. Our open-source work (Marker, Surya, Chandra) has more than 75,000 GitHub stars. Customers include Anthropic, ElevenLabs, Gamma, Reflection AI, and Legora, along with insurers, financial firms, and healthcare companies. We deploy anywhere from our API to fully air-gapped on-prem.

We're a small, founder-led team. You'll have real influence on how we sell and what we build.

Legal notes

Datalab is an equal opportunity employer. We do not discriminate on the basis of any characteristic protected by federal, state, or local law.

If you need an accommodation to participate in our hiring process, or if you believe you have experienced discrimination or harassment at any point in it, contact operations@datalab.to.

Read the job posting on the Datalab site

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Source: the Datalab Ashby job board. We last checked this job 8 h ago. We first saw it 4 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.

Datalab

Open tech jobs: 3
With posted pay: 100%

About Datalab: funding, hiring and pay

Compared with similar jobs

This base pay is above the median for AI research jobs in New York with no level in the job title.

Median: $223K a year
Other jobs in the group: 230

We compare the middle of each posted range. This is base pay as posted. The group does not include this job.