Job
Description
What you will do In this vital role We are looking for a creative and technically skilled Senior Software Engineer/AI Engineer Search to help design and build cutting-edge AI-powered search solutions for the pharmaceutical industry. In this role, you'll develop intelligent systems that surface the most relevant insights from clinical trials, scientific literature, regulatory documents, and internal knowledge assets. Your work will empower researchers, clinicians, and decision-makers with faster, smarter access to the right information. . Design and implement search algorithms using NLP, machine learning, semantic understanding, and deep learning models Build and fine-tune models for information retrieval, query expansion, document ranking, summarization, and Q&A systems Support integration of LLMs (e.g., GPT, BERT, Bio BERT) for semantic and generative search Train and evaluate custom models for biomedical named entity recognition, relevance ranking, and similarity search. Build and deploy vector-based search systems using embeddings and vector databases Work closely with platform engineers to integrate AI models into scalable cloud-based infrastructures (AWS, Azure, GCP) Package and deploy search services using containerization (Docker, Kubernetes) and modern MLOps pipelines. Preprocess and structure unstructured content such as clinical trial reports, research articles, and regulatory documents Apply knowledge graphs, taxonomies, and ontologies (e.g., MeSH, UMLS, SNOMED) to enhance search results Build and deploy recommendation systems models, utilize AIML infrastructure, and contribute to model optimization and data processing Experience in Generative AI on Search Engines Experience in integrating Generative AI capabilities and Vision Models to enrich content quality and user engagement Experience Generative AI tasks such as content summarization. deduping and metadata quality. Researching and developing advanced AI algorithms, including Vision Models for visual content analysis. Implementing KPI measurement frameworks to evaluate the quality and performance of delivered models, including those utilizing Generative AI. Developing and maintaining Deep Learning models for data quality checks, visual similarity scoring, and content tagging. Continually researching current and emerging technologies and proposing changes where needed. Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements. Basic Qualifications: Degree in computer science & engineering preferred with 6-8 years of software development experience 2-4 years of experience building AI/ML models, ideally in search, NLP, or biomedical domains. Proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers Experience with search technologies like Elasticsearch, OpenSearch, or vector search tools Solid understanding of NLP techniques: embeddings, transformers, entity recognition, text classification Hands-on experience with various AI models, GCP Search Engines, GCP Cloud services Proficient in programming language AI/ML, Python, Java Crawlers, Java Script, SQL/NoSQL, Databricks/RDS, Data engineering, S3 Buckets, dynamo DB Strong problem solving, analytical skills; Ability to learn quickly; Excellent communication and interpersonal skills Preferred Qualifications: Experience in AI/ML, Java, Python Experienced with Fast Pythons API, GraphQL Experience with design patterns, data structures, data modelling, data algorithms Experienced with AWS /Azure Platform, building and deploying the code Experience in Postgres SQL /Mongo DB SQL database, vector database for large language models, Databricks or RDS, S3 Buckets Knowledge of LLMs, generative AI, and their use in enterprise search Experience in Google cloud Search and Google cloud Storage Experience with popular large language models Experience with LangChain or LlamaIndex framework for language models Experience with prompt engineering, model fine tuning Knowledge of NLP techniques for text analysis and sentiment analysis Experience in Agile software development methodologies Experience in End-to-End testing as part of Test-Driven Development Good to Have Skills Willingness to work on Full stack Applications Exposure to MLOps tools like MLflow, Airflow, or SageMaker Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills. Ability to work effectively with global, remote teams. High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Strong presentation and public speaking skills.
