Senior Python AI Engineer

pdf.net is the fastest-growing product in our portfolio. Thanks to bold product breakthroughs, it already serves
hundreds of thousands of users every month
, and is on track for even greater growth.

We’re looking for a
Senior Applied AI Engineer
to build production-grade AI systems for document workflows at a massive scale. You will design and ship agentic, multimodal, evaluation-driven product features across extraction, reasoning, generation, and orchestration — owning everything from architecture and experimentation to latency, cost, reliability, and user impact.

This is a hybrid role that blends
custom model development
with
LLM API integration
to ship intelligent, production-ready features. You’ll work across the full lifecycle — from preparing training data and fine-tuning models, to designing retrieval pipelines and deploying performant inference systems in the cloud.

What You’ll Do

- Work on document intelligence problems:
OCR
, structured extraction, chunking, layout-aware parsing, and PDF-to-schema workflows.
- Design and ship
RAG pipelines
using vector databases, hybrid retrieval, reranking, and structured context assembly.
- Integrate hosted
LLM APIs
(
OpenAI
,
Anthropic
) and, where needed, smaller self-hosted models into product features.
- Build and fine-tune
transformer models
for classification, extraction, ranking, and generation tasks.
- Build scalable inference services using
vLLM
, batching, streaming, caching, and other latency/cost optimizations.
- Implement production pipelines for
training
,
evaluation
,
prompt/version management
, and
deployment
.
- Define and improve AI quality with offline evals, regression datasets, and task-level metrics for accuracy, latency, and reliability.
- Own AI-related infrastructure in
Docker
,
Cloud Run
, and
GCP
, with proper logging, monitoring, and observability.
- Collaborate with product, design, and full-stack engineers to ship user-facing AI features end to end.

What You Bring

- Strong
Python engineering
background with production-grade code, tests, and maintainable service architecture.
- Hands-on experience with
PyTorch
and
HuggingFace
, including training, fine-tuning, inference, and model debugging.
- Solid understanding of transformer internals, tokenization, embeddings, decoding strategies, and evaluation trade-offs.
- Experience integrating
OpenAI
/
Anthropic
APIs into real user-facing products, not just prototypes.
- Practical experience with
RAG systems
: chunking, embedding pipelines, vector search, reranking, context construction, and hallucination reduction.
- Experience with vector stores such as
pgvector
or
FAISS
; understanding of when retrieval helps and when deterministic pipelines are better.
- Familiarity with document understanding workflows:
OCR
, PDF parsing, table/form extraction, and normalization of messy real-world inputs.
- Experience building scalable inference or model-serving systems; familiarity with
vLLM
or similar serving stacks is a plus.
- Ability to debug model quality issues across prompts, retrieval, data, evaluation sets, and inference behavior.
- Comfortable owning systems in production: deployment, monitoring, incident debugging, and iterative improvement.

Bonus Points For

- Experience deploying ML/AI services with
Docker
on
GCP
(
Cloud Run
,
GKE
).
- Experience with
OpenTelemetry
,
Prometheus
,
Grafana
, or similar observability tooling.
- Experience with
Neo4j
or other graph-based knowledge systems where graph retrieval actually improves product behavior.
- Experience with
RLHF
, preference data, or ranking/reward modeling.
- Strong background in
document understanding
,
OCR
, and
structured PDF parsing
.
- Experience optimizing inference for latency and cost using batching, caching, routing, or speculative decoding.

Working with us

Pure Data-Driven SaaS

Learn and experiment, no opinion-driven decisions.

Location Independence

Work from a location that suits you - be it your home, a café, or anywhere else.

Unlimited Time Off

We trust you to take time off when you need, ensuring you’re always at your best when you’re with us.

Results-Oriented

We believe in the quality of output over hours clocked in. Deliver excellence, and enjoy unparalleled autonomy in return.

Salary & Contract

• Compensation: $60,000 — $132,000/year gross.
• Paid via deel.com (standard contract).
• Asia/Pacific or EU timezone.

How to apply?

• Submit via Google Forms (5-8 mins).
• After a successful resume review, you'll be invited for an interview. If needed, we may ask you to complete a short test assignment (2–4 hours maximum).