Fresher AI Engineer at WCG

Short Description:

The AI Engineer at WCG, based in Karnataka, India, holds a crucial role in revolutionizing clinical trial processes through advanced analytics solutions. They collaborate closely with cross-functional teams, leveraging cutting-edge AI/ML technologies to address diverse challenges in healthcare and clinical research. With expertise in generative AI, including LLM training and fine-tuning, the AI Engineer designs and implements machine learning models tailored to specific clinical trial needs. Their responsibilities span data collection, model development, evaluation, and visualization, ensuring accuracy, reliability, and robustness throughout the process. Committed to innovation and collaboration, the AI Engineer plays a pivotal role in driving positive impacts on healthcare outcomes.

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• Position: AI Engineer
• Location: Karnataka, India (Remote)
• Organization: WCG
• Job Type: Full Time - Regular

Job Summary

In the vibrant landscape of Data & Analytics (D&A) at WCG, the AI Engineer holds a pivotal position. Tasked with crafting analytics-driven solutions, the AI Engineer collaborates closely with the D&A engineering team and clinical trial specialists. Leveraging state-of-the-art AI/ML, Deep Learning, and LLM technologies, this role aims to revolutionize decision-making processes within clinical trials. Operating within a domain-agnostic framework, the AI Engineer engages with structured and unstructured data, developing algorithms and implementing innovative solutions tailored to diverse business needs. Integral to the D&A team, this role stays abreast of the latest advancements in the generative AI domain to align solutions with organizational objectives. Additionally, the AI Engineer documents best practices and collaborates with architecture and infrastructure teams on pattern development.

Education Requirements

• Advanced degree in a quantitative discipline with specialization in AI, particularly Neural Networks or Generative AI

Qualifications/Experience

• In-depth knowledge of generative AI, with expertise in LLM training, fine-tuning, and serving
• Proficiency in Python programming
• Strong familiarity with machine learning and deep learning frameworks such as TensorFlow and PyTorch
• Competence in SQL, data manipulation, and analysis tools like Apache Spark
• Exceptional problem-solving and analytical abilities
• Effective communication and teamwork skills
• Advantageous to have knowledge of healthcare and clinical trial processes
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Understanding of relational and non-relational databases
• Knowledge of big data technologies such as DataBricks, Hadoop, or Kafka
• Prioritization of data security

Essential Duties/Responsibilities

1. Data Collection and Integration: Collaborate with cross-functional teams to gather, cleanse, and integrate diverse healthcare and clinical trial data from multiple sources.

2. Machine Learning Model Development: Design, implement, and deploy machine learning and deep learning models addressing various clinical trial challenges, from patient recruitment to outcome prediction.

3. Data Processing: Develop data pipelines and workflows to preprocess and transform data for analysis and modeling purposes.

4. Modification and Fine-Tuning of Language Models: Adapt pre-trained language models for interaction with human users, integrating custom functions and external tool calling capabilities.

5. Alignment of Language Models: Tailor large language models based on user feedback or ad-hoc annotation processes.

6. Design and Implementation of Annotation Processes: Create ad-hoc annotation processes to enhance model training.

7. Model Training: Train LLM with authoritative data and documents sourced within the organization.

8. Model Evaluation: Conduct thorough testing and evaluation of machine learning models to ensure accuracy, reliability, and robustness.

9. Data Visualization: Develop interactive data visualizations and dashboards for effective communication of insights to technical and non-technical stakeholders.

10. Documentation: Maintain detailed documentation of data engineering and analytics processes, including code, model specifications, and best practices.

11. Research and Innovation: Stay updated on the latest advancements in AI and LLM technologies, exploring their potential applications in enhancing clinical trial processes.

12. Collaboration: Work closely with clinical experts, data scientists, and engineers to develop and implement solutions with tangible impacts on healthcare and clinical research.

13. Other Duties: Undertake additional responsibilities as assigned by supervisors, which may occasionally deviate from the primary role.

Travel Requirements

• 0% - 5%

WCG is committed to fostering an inclusive workplace and is proud to be an equal opportunity employer.

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