Talent Network Notice: This listing supports our ongoing worldwide talent pipeline for upcoming projects and future opportunities. It may not represent an immediate vacancy. Suitable candidates may be contacted when a relevant project becomes available.
Role Overview
We are developing AI-assisted features that help candidates understand, improve and present their professional information while helping employers discover relevant talent. In this role, you may design, evaluate and optimize machine-learning and language-model workflows that operate inside real product experiences.
What You'll Do
- Design and prototype AI/ML workflows for CV analysis, job matching, recommendations, ranking, text assistance and candidate intelligence.
- Evaluate model quality using practical benchmarks, test sets and product-oriented success criteria.
- Build retrieval, embedding, classification, extraction or ranking pipelines where they are more appropriate than freeform generation.
- Optimize model inference for latency, memory, cost and reliability across local, server and hybrid environments.
- Create structured outputs, guardrails, fallbacks and evaluation checks for AI-generated or AI-derived information.
- Work with product and engineering teams to integrate models into production applications and monitor their behaviour.
- Document assumptions, limitations and model decisions so AI features remain explainable and maintainable.
What We're Looking For
- Practical experience with Python and common machine-learning or NLP tooling.
- Understanding of modern LLMs, embeddings, retrieval, classification, evaluation and prompt/structured-output design.
- Ability to compare models using measurable criteria rather than relying only on subjective output quality.
- Knowledge of data preparation, experiment design and error analysis.
- Comfort working with APIs, data pipelines and production engineering teams.
- Awareness of privacy, bias, hallucination and reliability considerations in AI systems.
- Strong analytical thinking and clear technical communication.
Nice to Have
- Experience with open-source LLMs, quantization, llama.cpp, ONNX or other optimized inference runtimes.
- Vector databases, reranking, semantic search or recommendation-system experience.
- Experience with candidate/job data, HR-tech, career platforms or document intelligence.
- MLOps, model monitoring or production evaluation experience.
How We Work & What We Value
- Take ownership — raise risks early, follow through on commitments and care about the final result.
- Communicate clearly — remote work depends on useful updates, good documentation and respectful collaboration.
- Keep learning — we expect tools, AI capabilities and product requirements to keep changing.
- Solve the real problem — challenge unnecessary complexity and suggest better approaches when you see them.
- Respect users and their data — career information is sensitive and should be handled responsibly.
- Work pragmatically — quality matters, but so do prioritization, iteration and delivering useful outcomes.
Engagement Details
| | |
|---|---|
| Work model | Worldwide remote. |
| Engagement | Contract, project-based, hourly or another flexible arrangement depending on the project. |
| Experience | We may consider junior, mid-level and senior professionals depending on the scope of the opportunity. |
| Start timing | Upcoming projects and future opportunities; timing varies by project. |
| Compensation | Role- and project-specific. Scope, rate/compensation, expected availability and deliverables are agreed before an engagement begins. |
| Working pattern | Flexible where practical. Some projects may require agreed overlap hours, meetings, milestones or response windows. |
How to Apply
- Click Apply Now on the job page.
- Complete or review your candidate profile.
- Upload your current CV, or create/improve one using our free CV Builder if you need an updated version.
- Review your skills, experience and other application information, then submit your application.
Application review: We may use structured profile information and automated tools to help organize or evaluate applications. Automated scores or matching signals are supportive inputs only and do not guarantee an interview, project assignment or employment. Final decisions depend on the requirements of the relevant opportunity and appropriate review.
Equal Opportunity & Privacy
We welcome qualified professionals from different backgrounds and locations. We evaluate candidates based on relevant skills, experience, project requirements and suitability. Please submit only information you are comfortable using for recruitment and talent-network purposes, in line with our applicable privacy terms and your profile preferences.
