AI Engineer

Description

Description:

We are seeking a talented and driven AI Engineer to join our cross-functional AI innovation team within a leading pharmaceutical organization. You will work on designing, developing, and deploying GenAI-driven solutions, retrieval-augmented generation (RAG) systems, and scalable ML-powered applications across cloud-native environments to support drug development, regulatory, manufacturing, and commercial operations. The ideal candidate combines a strong academic foundation in machine learning with hands-on experience building real-world AI systems and full-stack applications that comply with the high standards of a regulated industry.

Essential Functions:

• Design and implement GenAI applications including LLM-integrated tools, RAG systems, and intelligent chatbots tailored for pharmaceutical functions such as R& D knowledge mining, regulatory intelligence, and medical information services.
• Build and optimize data ingestion, transformation, and semantic search pipelines using domain-specific embedding models (e.g., BioBERT, Ada-002).
• Develop and containerize AI services using FastAPI, Docker, and Kubernetes, deployed on AWS or Google Cloud Platform, ensuring adherence to data privacy and compliance standards (e.g., HIPAA, GxP).
• Collaborate with product, data, and platform engineering teams to integrate AI features into validated systems supporting clinical, quality, and manufacturing workflows.
• Contribute to end-to-end MLOps: model experimentation, deployment pipelines, audit readiness, monitoring, and performance tuning.
• Engineer full-stack applications (React + REST/GraphQL backends) with role-based access controls for internal and external scientific and business users.
• Support internal research and POCs on advanced topics like LLM reasoning, adverse event detection, pharmacovigilance, and digital biomarker analysis.

Requirements

Education:

• Bachelor's Degree (BA/BS) BS in Computer Science - Required
• Master Degree (MS/MA) M.S. in Computer Science (Machine Learning track) or equivalent experience - Preferred

Experience:

• 2 years or more in Experience in Python, SQL, and ML libraries like PyTorch, TensorFlow, scikit-learn.
• 2 years or more in Demonstrated experience with GenAI frameworks such as LangChain, Hugging Face, OpenAI APIs.
• 2 years or more in Exposure to healthcare or life sciences data, regulated environments, or ontologies like UMLS or SNOMED
• 2 years or more in Experience working in R& D or regulatory settings within the pharmaceutical or biotech industry
• 2 years or more in Experience with semantic search, LaTeX OCR pipelines, or financial/news sentiment models

Skills:

• A "builder's mindset" with a strong passion for translating AI research into useful tools in support of patient impact. - Intermediate
• Familiarity with MLOps workflows, DevOps tools (GitHub Actions, CI/CD), and cloud platforms (AWS, Google Cloud Platform) - Intermediate
• Experience with semantic search, LaTeX OCR pipelines, or financial/news sentiment models - Beginner

Specialized Knowledge:

• Proficiency in Python, SQL, and ML libraries like PyTorch, TensorFlow, scikit-learn.
• Demonstrated experience with GenAI frameworks such as LangChain, Hugging Face, OpenAI APIs
• Experience developing cloud-native microservices using FastAPI, Flask, and deploying via Docker/K8s
• Familiarity with MLOps workflows, DevOps tools (GitHub Actions, CI/CD), and cloud platforms (AWS, Google Cloud Platform)

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