Senior AI Engineer (OCR/VLM focus)

Lalamove is hiring a Senior AI Engineer (OCR/VLM focus). Level rates it ; you can apply on Lalamove.

Level's read on this job

On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include computer vision, NLP and speech.
Level classifies it as a senior role.
Level lists 142 other open roles at Lalamove.

AI in this role

computer-visionnlpspeech

At Lalamove, we believe in the power of community. Millions of drivers and customers use our technology every day to connect with one another and move things that matter. Delivery is what we do best and we ensure it is always fast and simple. Since 2013, we have tackled the logistics industry head on to find the most innovative solutions for the world’s delivery needs. We are full steam ahead to make Lalamove synonymous with delivery and on a mission to impact as many local communities we can. We have massively scaled our efforts across Asia and now have our sights on taking our best in class technology to the rest of the world. And we are looking for talented professionals to join us in this journey!! We are seeking a Senior AI Engineer to join our Data Science Team at Lalamove.

What you'll do

What you’ll do:
Collaborate with a team of data scientists and machine learning engineers to develop and deploy stable machine learning services in production.
Support the team to create ML solutions that empower and enhance organizational success globally by closely collaborating with other teams and departments.
Be responsible for making our products and services intelligent by developing and deploying data-driven solutions.
Tackle a variety of challenges using your machine learning expertise, such as:
Computer Vision and VLM Applications
NLP and Generative AI Applications
Structured Data Modelling
Monitor and evaluate the effectiveness and healthiness of our solutions.
Research state-of-the-art machine learning technologies to identify potential benefits for the company.

What you'll need:

More than 5 years of hands-on experience implementing high availability production machine learning systems.
Experienced in Computer Vision, LLM, VLM, OCR, Vector Databases. Experience with Automatic Speech Recognition and Text-To-Speech is a plus.
Experienced in building and deploying production-ready machine learning services.
Good command of English and Mandarin.

To all candidates- Lalamove respects your privacy and is committed to protecting your personal data.This Notice will inform you how we will use your personal data, explain your privacy rights and the protection you have by the law when you apply to join us. Please take time to read and understand this Notice. Candidate Privacy Notice: https://www.lalamove.com/en-hk/candidate-privacy-notice

How we rate this

Senior AI Engineer (OCR/VLM focus) at Lalamove rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior AI Engineer (OCR/VLM focus) is an open job at Lalamove.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Hong Kong SAR.
The job was posted on April 30, 2026.
Seniority: senior.
Applications are handled by Lalamove. Apply on Lalamove

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPSpeech

Also common in AI engineer jobs at this level

Python AI agents AWS Azure RAG Google Cloud

Pay

Typical AI engineer job: $184k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
What have you built with speech recognition or text-to-speech, and where did it break?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, and Speech. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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