Machine Learning / GenAI Engineer
OUR COMPANY
RegASK is an AI-driven solution enabling end-to-end intelligent regulatory workflow orchestration: automating regulatory intelligence with curated content and actionable insights, smart documentation and a connected community of over 1,700+ subject matter experts for streamlined regulatory execution globally. RegASK augments Regulatory Affairs teams, combining AI efficiency and community-driven intelligence to streamline compliance across the product lifecycle. The RegASK team is highly diverse, with more than 10 nationalities across 3 continents, entrepreneurial and very agile. We are currently recruiting highly motivated individuals to expand its team and support its ambitious growth plans.
If you are a doer who enjoys working across industries and continents, autonomous in your working style, and eager to problem solve, we would love to hear from you.
We are looking for a mid-to-senior Machine Learning / GenAI Engineer – LLM Production & Deployment to join our Data Science team. In this role, you will leverage cutting-edge Large Language Model (LLM) techniques and GenAI architectures to solve real-world business challenges. You will work cross-functionally with engineering and product teams to design, develop, and deploy scalable ML solutions that enhance decision-making and automate complex language-driven workflows.
Responsibilities:
- Lead and or participate in the design/architecture and deployment of GenAI/NLP-based solutions, including LLM fine-tuning, RAG, embedding optimization, and vector store integrations
- Collaborate with business stakeholders to gather requirements and translate them into scalable ML/LLM application/data pipelines
- Own the lifecycle of ML models: from experimentation, data preparation to deployment and monitoring in production (DevOps for LLM and ML based applications)
- Develop and maintain prompt pipelines and agentic workflows using LangChain, LangGraph, and LangSmith.
- Design data ingestion and vectorization strategies for large-scale unstructured content
- Stay current with the latest ML and GenAI research and evaluate their applicability to RegASK's use cases
- Support model interpretability and communicate outcomes to business and regulatory experts
- Mentor junior team members and contribute to internal tooling and best practices
- Strong understanding of NLP and deep learning architectures (Transformers, BERT, Autoencoders, RNNs, GANs).
- Hands-on experience with GenAI applications: embeddings, LLM fine-tuning (LoRA, QLoRA, DPO, RLHF), vector databases, prompt engineering, agentic AI workflows.
- Experience deploying ML/LLM applications in production (MLOps/LLMOps), especially in Azure: ML Studio, Azure OpenAI, Azure AI Foundry.
- Proficiency in Python and scientific libraries (Transformers, spaCy, LangChain, LangGraph, FastAPI).
- Experience with SQL and NoSQL data modeling.
- Strong understanding of software engineering best practices and hands on DevOps for ML.
- Excellent communication skills — ability to explain complex principles/notions to non-technical stakeholders.
- Manage and lead business requirements discussions.
- Proven experience managing GenAI or ML pipelines end-to-end.
- Bonus: background in compliance, life sciences, or regulatory intelligence
- Flexible working arrangements (hybrid)
- An opportunity to drive impact at the intersection of AI, SaaS, and regulatory intelligence.
- Continuous learning and professional development
If you are excited about this opportunity and believe you have the skills and qualifications to excel as our Machine Learning / Gen AI Engineer, please submit your resume for consideration.
We appreciate all applications, but only selected candidates will be contacted for an interview.
Thank you for considering joining the RegASK team. We look forward to reviewing your application!