Full Stack Developer

3 days ago

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BioVid

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BioVid is a strategic consulting firm that partners with life science organizations to enhance their understanding of human behavior, enabling more effective customer interactions. Through a combination of innovative research, sophisticated analytics, and design, BioVid helps leading pharmaceutical and medical device companies navigate complex market dynamics and minimize risks in clinical trials. By utilizing evidence-based techniques and a deep understanding of cognitive and behavioral science, BioVid empowers clients to make accurate predictions and informed business decisions that support the greater good.

Primary Global Healthcare Market Research • Quantitative Research (50%) • Qualitative Research (50%) • Cognitive Marketing • Cognitive Insights

51 - 200 employees

Founded 1998

🧬 Biotechnology

💊 Pharmaceuticals

⚕️ Healthcare Insurance

📋 Description

• As a full stack developer responsible for designing, developing, and maintaining web-based applications and data platforms supporting research operations. • Work across the software stack, ensuring seamless data integration and workflow automation. • Collaborate with cross-functional teams to deliver innovative and scalable solutions. • Design, develop, and maintain scalable APIs and microservices using JavaScript and Python. • Deploy, manage, and optimize applications on cloud platforms. • Work with Large Language Models and implement AI-driven features. • Ensure system scalability, reliability, and security through infrastructure best practices. • Continuously analyze and improve system performance.

🎯 Requirements

• Knowledge of model deployment tools and platforms (cloud platforms like AWS, GCP, Azure, containerization like Docker, Kubernetes). • Strong programming skills (Python, etc.) • Understanding of security best practice for cloud environments. • Monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack). • Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation). • Deep understanding of LLM architectures (Transformer, etc.) and NLP techniques. • Experience with LLM APIs (e.g., OpenAI, Cohere, Hugging Face) and frameworks (e.g., TensorFlow, PyTorch). • API development and integration experience. • MLOps principles and tools. • CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI). • Containerization and orchestration (Docker, Kubernetes).