Title
NLP Engineer
Quick Summary
Polylogue Systems is hiring an NLP Engineer to design, build, and productionize language understanding features that power classification, extraction, summarization, and semantic search across our SaaS platform. You will turn research ideas into reliable APIs, partner with product and platform teams, and measure impact through clear metrics. We welcome strong graduates and early-career engineers with hands-on projects, while offering growth paths and senior mentorship.
Project Category or Industry
Artificial intelligence for SaaS, information retrieval, and knowledge management.
Type
Full-time employment.
Experience Level
Entry to mid-level. Freshers with solid portfolios and internships are encouraged; experienced engineers are welcome.
Duration
Permanent role.
Location
Remote-first with optional collaboration hubs in Lisbon and Singapore. Maintain at least four hours of overlap with teams operating between UTC−1 and UTC+8.
Salary
USD 86,000–125,000 base depending on location and experience, plus benefits and an annual performance bonus.
Payment Mode
Monthly payroll where supported; compliant contractor arrangements available in select countries.
Hiring Company Name
Polylogue Systems
Required Skills or Tools
Strong Python and software engineering fundamentals; practical knowledge of modern NLP stacks; comfort with embeddings, vector search, and evaluation; and the ability to ship observable, well-tested services. Familiarity with cloud platforms and CI/CD will help you move quickly.
Project Description
Polylogue Systems builds language intelligence that helps users search, organize, and act on unstructured content. As an NLP Engineer, you will scope opportunities with product managers, prototype models and pipelines, and harden them for production with the reliability and observability required in enterprise environments. The work spans dataset creation, modeling, offline and online evaluation, and close collaboration with MLOps to ensure safe, predictable releases.
Core Responsibilities and Expected Deliverables
Design and implement models for classification, NER, summarization, topic modeling, and ranking.
Build retrieval pipelines with robust chunking strategies, embeddings, and query rewriting; define success metrics and guardrails.
Develop offline/online evaluation harnesses with golden datasets, regression tests, and error analysis workflows.
Expose models via well-documented APIs and batch jobs; ensure low latency, scalability, and resilience.
Instrument quality, drift, and latency dashboards; deliver runbooks and incident response procedures.
Produce reproducible training code, experiment reports, and concise documentation for cross-functional stakeholders.
Required Experience and Preferred Qualifications
Proficiency in Python with testing, code review, and version control best practices.
Experience with one or more of PyTorch, TensorFlow, or JAX; working knowledge of scikit-learn and spaCy.
Comfort with SQL and data warehouses; familiarity with feature engineering and embeddings.
Preferred: experience with Hugging Face Transformers, vector databases (FAISS or pgvector), Elasticsearch or OpenSearch, and prompt-tuned LLM components where appropriate.
Coursework, internships, or open-source contributions showing practical impact will be valued.
Tools or Platforms to Be Used
Modeling and experimentation: PyTorch or TensorFlow, Hugging Face, spaCy, scikit-learn, MLflow or Weights & Biases.
Retrieval and storage: FAISS or pgvector, Elasticsearch or OpenSearch, Postgres or BigQuery.
Services and infrastructure: FastAPI, Docker, Kubernetes, GitHub Actions, AWS or GCP, Terraform with platform support.
Observability: Prometheus, Grafana, OpenTelemetry-compatible logging; prompt and model evaluation toolkits.
Language Requirement
Professional English is required. Additional languages are helpful for cross-regional collaboration.
Communication Style
Written-first culture using GitHub issues and pull requests for design and reviews; Slack for daily coordination; Zoom for stand-ups, demos, and incident retrospectives.
Time Commitment or Working Window
Standard 40 hours per week with flexible scheduling. Maintain a predictable daily block overlapping at least four hours with the core team between 09:00 and 17:00 in your local time.
Payment Terms
Salary paid monthly via payroll. For contractors, invoices are processed on net-30 terms upon acceptance of deliverables and timesheets.
Evaluation Criteria
Portfolio and code samples demonstrating modeling rigor, evaluation discipline, and shipping reliability.
Practical exercise focused on building and evaluating an NLP pipeline with retrieval and guardrails.
Technical interview on observability, error analysis, and performance/cost trade-offs.
Final conversation on collaboration, product sense, and communication.
References may be requested.
Other Requirements
New hires sign a confidentiality agreement and adhere to security and data-handling policies. Light time-tracking may be used for distributed coordination. Occasional shared on-call for NLP platform updates may be required.
About Polylogue Systems
Polylogue Systems is a privately held software company focused on AI-enabled knowledge tools for teams in financial services, healthcare, and professional services. Headquartered in Lisbon with a distributed workforce across EMEA and APAC, we combine rigorous engineering with applied research to deliver reliable language understanding at scale. Learn more at https://www.polylogue.systems and reach our hiring team at [email protected].