Consultant, AI Engineer
AI summary
PATH seeks an AI Engineer to scale SnapiForm, an AI platform digitizing health forms. Role involves computer vision, VLM pipelines, and deploying cost-efficient AI systems for low-resource settings. Requires 7+ years ML experience with focus on computer vision/Document AI.
- Develop and optimize computer vision and VLM pipelines for health data
- Work on scaling AI for low-resource settings with 10 million forms target
- Requires 7+ years ML engineering, PyTorch, Hugging Face expertise
AI job guide
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AI salary guide
Not enough public dataNot enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.
Can you qualify for this role?
- Required7+ years of relevant experienceThe job post includes a minimum experience signal.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in technology, AI Engineer, Machine Learning EngineerThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in AccraThe vacancy is associated with this location.
Documents to prepare
- Likely requiredUpdated CV
- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
- VerifyID or passport only after verifying the employer
Application tips for this job
- Place your strongest Consultant, AI Engineer evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to Jobberman Ghana and the role in Accra.
- Add concrete examples related to technology, AI Engineer, Machine Learning Engineer, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from Jobberman Ghana; avoid sending documents to unofficial contacts or copied links.
- Confirm the deadline, interview location and employer contact before sharing personal documents.
- Prepare a polite question about pay, benefits and contract terms for later interview stages.
Source and safety check
- Jobberman Ghana
- Original source link available
- Application method is clear
- Deadline not specified
- No major risk signal was detected in the captured text.
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Interview preparation
- What experience makes you a strong fit for this Consultant, AI Engineer role in technology, AI Engineer?
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- Are you available to work in Accra under the listed contract or schedule?
- Prepare examples with clear responsibilities, tools used and measurable outcomes.
- Review the source and research Jobberman Ghana before the interview.
Ask what the first priorities will be in the role and how success will be measured.
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Original source description
Location: Ghana Job descriptions &
Find a Job + + + + Search P Consultant, AI Engineer PATH Software & Data 3 weeks ago Accra & Tema Region IT & Telecoms Confidential Share link Share on WhatsApp Share on LinkedIn Share on Facebook Share on Twitter Share via SMS Language Requirement: English Working Hours: 8 to 5 Applicant
Requirements
PATH current employees - please log in and apply PATH is a global nonprofit dedicated to achieving health equity. With more than 40 years of
Experience
forging multisector partnerships and with expertise in science, economics, technology, advocacy, and dozens of other specialties, PATH develops and scales up innovative solutions to the world’s most pressing heath challenges. PATH is seeking an AI Engineer to help scale SnapiForm, an AI-powered platform available through Telegram mini-app, WhatsApp and the browser that enables health workers to digitize paper HMIS forms by simply taking a photo. Following a successful pilot in the DRC that significantly improved data accuracy and reduced reporting time, SnapiForm is now expanding to process millions of health records each month. In this role, you will develop and optimize computer vision and Vision-Language Model (VLM) pipelines for handwriting recognition, table extraction, and structured data parsing, while building scalable and cost-efficient AI systems for low-resource health settings.
7+ years of
in Machine Learning Engineering, with at least 1-2 years specifically focused on Computer Vision, Document AI, or Multimodal Large Language Models. Core Frameworks : Deep expertise in PyTorch and the Hugging Face ecosystem (Transformers, PEFT). Inference Engines : Hands-on, production-level
deploying models using vLLM. Domain Expertise : Proven
working with Document AI, Optical Character Recognition (OCR), Handwriting Recognition (HTR), or Vision-Language models. Image Processing : Proficiency in computer vision libraries (OpenCV, Pillow) and
handling real-world, variable-quality mobile images, including tiling and chunking strategies. Infrastructure & Cloud : Strong
with Docker, Kubernetes, and cloud GPU provisioning. Familiarity with distributed training and inference optimization. Programming : Exceptional Python skills, with
writing clean, modular, and highly optimized code. Language : Fluency in verbal and written English Personal Attributes: Passionate about building technology that improves health systems and supports frontline health workers in low-resource settings. Strong focus on building cost-effective, scalable AI solutions that perform well on limited hardware. Able to balance cutting-edge AI research with practical engineering decisions and real-world constraints. Proactive and able to work independently as well as collaboratively. Strong sense of accountability and commitment to continuous improvement. What We Offer: Opportunity to contribute to impactful digital health and data initiatives. Competitive compensation and flexible working arrangements. Log In and Apply Important safety tips Do not make any payment without confirming with the Jobberman Customer Support Team. If you think this advert is not genuine, please report it via the Report Job link below. Report Job Log in to apply now Continue with Google Continue with Linkedin Or continue with Forgot Password? Keep me logged in Log in Don't have an account? Sign Up to Apply Share link Share on WhatsApp Share on LinkedIn Share on Facebook Share on Twitter Share via SMS Activate Notifications Stay productive - get the latest updates on Jobs & News Activate Deactivate Notifications Stop receiving the latest updates on Jobs & News Deactivate This action will pause all job alerts. Are you sure? Cancel Proceed Similar jobs Lorem ipsum dolor sit amet consectetur adipiscing elit Lorem ipsum Lorem ipsum dolor (Location) Lorem ipsum Confidential 3 years ago Lorem ipsum dolor sit amet consectetur adipiscing elit Lorem ipsum Lorem ipsum dolor (Location) Lorem ipsum Confidential 3 years ago View More Stay Updated Join our newsletter and get the latest job listings and career insights delivered straight to your inbox. v2.homepage.newsletter_signup.choose_type Jobseeker Employer Email address * We care about the protection of your data. Read our Notify Me We care about the protection of your data. Read our privacy policy .
Responsibilities
Design and optimize AI pipelines for complex document understanding. Focus on extracting structured data from mobile-captured HMIS forms, specifically tackling challenges like handwriting recognition, complex table extraction, and multilingual parsing. Research, benchmark, and fine-tune state-of-the-art Vision-Language models (e.g., Qwen-VL) and foundational OCR models on domain-specific datasets. Utilize advanced techniques (LoRA/QLoRA, DeepSpeed) to maximize accuracy on noisy, real-world mobile images. Architect and deploy production-grade inference pipelines using vLLM or similar engines. Optimize continuous batching, KV cache management, and quantization to maximize throughput while strictly maintaining our low per-page processing cost targets. Design architecture for both self-hosted/local cloud environments (like Linode) and on-premise hardware, keeping data sovereignty and cost efficiency in mind. Tune AI models for visual data optimization. Develop strategies for image chunking, tiling, and preprocessing to allow models to efficiently process high-resolution images and large, complex tables without losing context. Evaluate, select, and provision optimal cloud and on-prem GPU infrastructure to handle a target volume of 10 million forms. Assess next-generation hardware (e.g., NVIDIA Blackwell nodes) to balance massive scalability, performance, and budget efficiency. Lay the technical groundwork for future iterations, including offline/edge processing support, expanded multilingual capabilities, and interoperability beyond DHIS2. Willingness to travel to PATH countries as needed and overlap with GMT and ESA timezones Required Qualifications and
Education
B.S. or M.S. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.