General Information

Location: Karnataka, India, Remote

Organization: WCG

Job Type: Full Time - Regular

Description and Requirements

In our Data & Analytics (D&A) organization, the AI Engineer plays a pivotal role in the development of analytics-driven solutions that optimize and streamline end-to-end clinical trial processes. Working closely with our D&A engineering team and clinical trial experts, this role will harness the power of cutting-edge AI/ML, Deep Learning, and LLM (Large Language Models) technologies to provide AI-based solutions, enhancing decision-making in the clinical trial process. The AI Engineer is part of a team that is domain agnostic, working hands-on with structured as well as unstructured data, designing algorithms and implementing innovative capabilities that cater to an array of business use cases within our D&A function. As a core member of the D&A team, the AI Engineer leverages the power of latest developments, tools, and libraries in the generative AI field to deliver clinical trial business solutions that are aligned to the organization’s strategic roadmap. The AI Engineer will also document best practices and work with the architecture and infrastructure teams on developing patterns.

  • Advanced degree in a quantitative discipline (i.e. statistics, applied mathematics, computer science, data mining, machine learning, or some other empirical science) with specialization in AI, particularly Neural Networks or Generative AI
  • High scientific understanding of generative AI including broad knowledge in the field of AI and specific knowledge in LLM training, fine-tuning and serving
  • Strong programming skills, particularly in Python
  • Proficiency with machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch)
  • Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache Spark)
  • Excellent problem-solving and analytical skills
  • Strong communication and teamwork skills
  • Knowledge of healthcare and clinical trial processes is a plus
  • Familiarity in a cloud platform (AWS, Azure, or GCP)
  • Familiarity with relational and non-relational databases and how they work
  • Familiarity with big data technologies such as DataBricks, Hadoop, or Kafka
  • Possess a data security mindset
ESSENTIAL DUTIES/RESPONSIBILITIES: To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The accountabilities listed below are representative of the knowledge, skills, and/or ability required.
  • Data Collection and Integration: Collaborate with cross-functional teams to collect, clean, and integrate diverse healthcare and clinical trial data from various sources.
  • Machine Learning Model Development: Design, develop, and implement machine learning and deep learning models to address specific challenges in clinical trials, such as patient recruitment, data analysis, protocol study, anomaly detection, document entity extraction, document generation, translation, and outcome prediction.
  • Data Processing: Create data pipelines and workflows to preprocess and transform data into a format suitable for analysis and modeling.
  • Modify and fine-tune pre-trained language models to make them interact with human users.
  • Engineer and equip large language models with custom functions and with the ability to call external tools.
  • Align large language models based on feedback from users or from ad-hoc annotation process.
  • Design ad-hoc annotation process.
  • Train LLM with authoritative data and documents from within the organization.
  • Model Evaluation: Conduct rigorous testing and evaluation of machine learning models, ensuring accuracy, reliability, and robustness.
  • Data Visualization: Develop interactive data visualizations and dashboards to communicate insights and outcomes to both technical and non-technical stakeholders.
  • Documentation: Maintain detailed documentation of data engineering and analytics processes, including code, model specifications, and best practices.
  • Research and Innovation: Keep current on the latest advancements in AI and LLM technologies and explore their potential applications in improving clinical trial processes.
  • Collaboration: Work closely with clinical experts, data scientists, and engineers to develop and deploy solutions that directly impact the healthcare and clinical research industry.
  • Other duties as assigned by supervisor. These may, on occasion, be unrelated to the position described here.