> Markdown version of [/jobs/ext/3204452-senior-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3204452-senior-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML Engineer - **Company:** PRUDENTIA SCIENCES, INC. - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $206,000.0 - $240,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Rapid Prototyping Process, Tensorflow, Software Engineering, Web Services, Cloud Platform System, Chatbots, Data Ingestion, Large Language Models, Snowflake, Apache Spark, Generative AI, Containerization, Information Technology, Non-relational Database, Data Management, Machine Learning Operations, Software Coding, Docker, Databricks - **Published:** September 9, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3742efecc003f285 ## About the Role We're looking for a driven, hands-on Senior ML/AI Engineer to help us push the boundaries of what's possible in AI-driven drug development. You'll work on production-grade LLM-based systems, knowledge graphs, and machine learning pipelines-turning prototypes into powerful tools that make a real-world impact., * Education: Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, or a related field. * Hands-on AI Experience: Proven ability to build, train, and deploy ML and NLP models, especially those powered by LLMs and transformer architectures. * LLM & LangChain Experience: Practical experience working with frameworks like LangChain for applications such as Q&A systems, chatbots, or document automation. * Software Engineering: Strong coding skills in Python and experience using Git/GitHub and CI/CD practices. * Data Engineering Know-how: Comfort working with ETL pipelines, relational and non-relational databases, and data platforms like Snowflake or Databricks. * Big Data & ML Frameworks: Familiarity with Big Data tools (e.g., Apache Spark) and experience orchestrating data workflows using tools like Apache Airflow. * Cloud & MLOps: Experience with deploying ML models in cloud environments (AWS, GCP, or Azure) and using containerization/orchestration tools like Docker and Kubernetes. Soft Skills: * 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. Bonus: * Experience in healthcare, life sciences, or biopharma sectors (preferred but not required). ## Description You'll collaborate across teams to design, build, and deploy intelligent systems that enhance how life sciences organizations make critical decisions. If you love working on technically challenging problems with direct impact in healthcare-this is the role for you., * 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. ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Testing AI Agents: Automated Evaluation for Chatbots & RAG Systems](https://www.wearedevelopers.com/videos/100300-testing-ai-agents-automated-evaluation-for-chatbots-rag-systems) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)