Senior Applied AI Engineer at GSK delivering high - impact AI/ML solutions aligned with R&D priorities. Collaborating with cross - functional teams to build and deploy machine learning models for drug discovery.
About the role
- Entry-level AI Engineer responsible for developing, testing, and deploying ML and LLM-based solutions. Supporting foundational engineering skills across AI spectrum in a hybrid work environment.
Responsibilities
- Support data collection, cleaning, and preprocessing for ML and LLM projects.
- Assist in implementing, evaluating, and optimizing AI/ML models and LLM pipelines.
- Develop and test prompt templates, retrieval chains, and agentic components under guidance.
- Contribute to fine-tuning and lightweight adaptation (LoRA, adapters, instruction-tuning) of models.
- Implement model APIs or inference endpoints, and integrate them into applications or microservices.
- Participate in debugging, troubleshooting, and monitoring both ML pipelines and agentic workflows.
- Document data flows, model architectures, and experiment results clearly.
- Stay current with advances in machine learning, generative AI, and agent frameworks (LangChain, LangGraph, vLLM etc.).
Requirements
- Education: Bachelor’s in Computer Science, AI, ML, Data Science, Electrical Engineering, or related field.
- Experience: 0 to 3 years in software development or academic AI/ML projects.
- Technical Skills
- Solid programming skills (Python, R, Java, C++).
- Understanding of ML concepts (supervised/unsupervised learning, evaluation metrics).
- Familiarity with LLM ecosystems (OpenAI API, Hugging Face, LangChain).
- Exposure to fine-tuning and prompt engineering.
- Knowledge of data structures, algorithms, and Git.
- Basic understanding of MLOps / AgentOps workflows.
- Soft Skills
- Curiosity, teamwork, and proactive learning attitude.
- Analytical mindset with good communication skills.
- Customer-centric thinking and disciplined work ethic.
Job title
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