Senior AI Engineer (Applied AI / ML)
Company: Radvin
Job Type: Full-time
About Radvin
Radvin is an enterprise software company building intelligent HR platforms that combine automation, analytics, and AI-driven decision support. Our AI systems power document intelligence, recruitment automation, predictive analytics, smart reminders, and advanced reporting.
We are looking for a Senior AI Engineer who can design, build, and productionize real-world AI systems, not just models — with a strong focus on reliability, testing, scalability, and ethical AI. Making sure we both wokr on API from LLMs and local computed LLM.
Responsibilities
- Design and implement AI/ML solutions across multiple HR domains
- Develop NLP pipelines for resumes, HR documents, emails, and system text
- Build document intelligence systems (OCR, classification, entity extraction, tagging)
- Implement predictive analytics models (employee turnover, performance, hiring success)
- Develop AI-driven recruitment features (CV parsing, candidate scoring, ranking, clustering)
- Build intelligent reminder and alert systems with personalized timing and escalation logic
- Integrate ML models into production backend services (APIs, batch jobs, pipelines)
- Design and maintain end-to-end ML pipelines from data ingestion to inference
- Monitor models in production and handle data drift, model drift, and retraining
- Collaborate closely with backend, frontend, and product teams
- Contribute to architectural decisions and mentor junior engineers
Testing & Quality (Mandatory)
AI at Arvin must be testable, measurable, and production-ready.
You will be expected to:
- Write unit tests for data pipelines, feature engineering, and model logic
- Apply property-based testing for data and ML assumptions
- Design and maintain integration tests between AI components and backend services
- Implement end-to-end (E2E) testing for ML pipelines
- Perform regression testing to ensure model updates do not degrade performance
- Use A/B testing to compare models and measure real-world impact
- Implement context-based testing (user segments, departments, scenarios)
- Contribute to:
- Functional and non-functional testing
- Performance testing (latency, throughput)
- Security testing (data access, model exposure)
- System and acceptance testing
- Ensure all AI workflows are automated in CI/CD pipelines
Required Skills & Experience
- 5+ years of experience in AI / Machine Learning / Applied Data Science
- Strong proficiency in Python
- Solid experience with machine learning algorithms and statistics
- Hands-on experience with NLP (spaCy, transformers, text classification, NER)
- Experience with OCR and document processing (Deepseek OCR)
- Experience with scikit-learn, Pandas, NumPy
- Experience building production ML systems, not just experiments
- Strong understanding of model evaluation, validation, and explainability
- Experience with Git and collaborative development
- Ability to write clean, maintainable, and well-documented code
Nice to Have (Plus)
- Experience with Deep Learning frameworks (PyTorch or TensorFlow)
- Familiarity with MLOps practices (MLflow, model monitoring, retraining)
- Experience with Kafka or streaming data pipelines
- Experience integrating AI with backend frameworks (Django, FastAPI)
- Knowledge of data privacy, fairness, and ethical AI
- Experience with Docker, CI/CD, and deployment workflows
- Familiarity with analytics dashboards and visualization tools
What We Offer
- Work on end-to-end AI systems with real business impact
- High technical standards and engineering ownership
- Opportunity to shape AI architecture across the platform
- Professional, product-focused engineering culture
- Competitive salary based on experience
- Stable, long-term product vision