Note: The job is a remote job and is open to candidates in USA. Prudentia Sciences is an AI-powered technology platform transforming how biopharma, biotech, and life sciences investors approach portfolio management, due diligence, and value/risk simulation. They are seeking a driven, hands-on ML/AI Engineer to help push the boundaries of AI-driven drug development by designing, building, and deploying intelligent systems that enhance decision-making in life sciences.
Responsibilities
- Design and Deploy LLM Systems: Develop scalable, production-ready LLM applications using frameworks like LangChain/LangGraph. Build robust RAG pipelines and integrate knowledge graphs for biological and clinical data
- Full-Stack AI Engineering: Write maintainable, high-performance code and build clean APIs and services for machine learning applications
- Data Engineering Collaboration: Work with data engineers to build and optimize data workflows and pipelines for high-quality data ingestion and processing
- Product-Focused Prototyping: Collaborate with product and domain teams to rapidly prototype AI solutions, iterate based on feedback, and scale models for production
- Model Deployment & MLOps: Use modern MLOps tools to deploy and monitor models in production environments (AWS preferred). Ensure scalability, observability, and resilience
- Collaborative Innovation: Partner with engineering, data, and business teams to identify and develop high-value AI/ML applications
- Continuous Learning: Stay ahead of the curve on emerging ML frameworks, GenAI capabilities, and healthcare technologies
Skills
- Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, or a related field
- Proven ability to build, train, and deploy ML and NLP models, especially those powered by LLMs and transformer architectures
- Practical experience working with frameworks like LangChain for applications such as Q&A systems, chatbots, or document automation
- Strong coding skills in Python and experience using Git/GitHub and CI/CD practices
- Comfort working with ETL pipelines, relational and non-relational databases, and data platforms like Snowflake or Databricks
- Familiarity with Big Data tools (e.g., Apache Spark) and experience orchestrating data workflows using tools like Apache Airflow
- Experience with deploying ML models in cloud environments (AWS, GCP, or Azure) and using containerization/orchestration tools like Docker and Kubernetes
- Strong problem-solving skills and an analytical mindset
- Passion for continuous learning, rapid prototyping, and iterating based on user needs
- Autonomous, self-starter attitude with a strong sense of ownership
- Excellent communication skills—able to explain technical ideas clearly to non-technical audiences
- Collaborative team player with a desire to build things that truly matter
- Experience in healthcare, life sciences, or biopharma sectors (preferred but not required)
Benefits
- Competitive salary, equity, and benefits
- Opportunity to grow with a fast-moving, well-funded startup backed by top-tier investors
- Competitive salary, performance bonus, and equity
- Collaborative, mission-driven colleagues passionate about transforming biopharma
- Enjoy flexibility and autonomy in a remote-first culture
Company Overview