Description :

About the Role :

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of advanced AI and machine learning solutions for complex challenges in the life sciences domain. This role requires deep technical expertise across AI/ML methodologies, cloud-native architecture, and scalable data platforms, combined with strong leadership and strategic thinking.

As an AI/ML Architect, you will define end-to-end AI/ML system architectures, guide engineering teams, and collaborate with domain experts to translate scientific and business problems into impactful AI-driven solutions.

Key Responsibilities :

- Lead the end-to-end design and implementation of scalable, secure, and compliant AI/ML architectures.

- Define reference architectures and best practices for model development, training, deployment, and monitoring.

- Select appropriate AI/ML algorithms, frameworks, and tools based on problem complexity and data characteristics.

- Ensure architectures support high availability, performance, and cost efficiency.

- Design and guide implementation of models using :

1. Supervised and unsupervised learning

2. Deep learning (CNNs, RNNs, Transformers)

3. Natural Language Processing (NLP)

4. Time-series analysis and predictive modeling

- Apply AI/ML techniques to life sciences use cases such as :

1. Drug discovery and development

2. Clinical trial optimization

3. Genomics and bioinformatics

4. Pharmacovigilance and real-world evidence

- Provide hands-on guidance and review of model development in Python and R.

- Architect and deploy AI/ML solutions on major cloud platforms (AWS, Azure, or GCP).

- Design and implement MLOps pipelines for :

1. Data ingestion and feature engineering

2. Model training, validation, and versioning

3. Model monitoring, retraining, and governance

- Leverage containerization and orchestration technologies (Docker, Kubernetes) for scalable deployments.

- Collaborate with data engineering teams to design data pipelines and feature stores.

- Ensure efficient handling of structured, semi-structured, and unstructured datasets.

- Implement data governance, lineage, and quality frameworks.

- Ensure AI/ML solutions comply with life sciences regulatory standards (e.g., GxP, HIPAA, GDPR).

- Implement model explainability, bias detection, and auditability.

- Establish model governance frameworks, including documentation and validation processes.

- Act as a technical leader and mentor to AI/ML engineers and data scientists.

- Collaborate closely with product owners, life sciences SMEs, cloud engineers, and stakeholders.

- Translate complex technical concepts into business-relevant insights.

- Contribute to AI strategy, roadmap planning, and innovation initiatives.

- Stay current with the latest AI/ML research, tools, and industry trends.

- Evaluate emerging technologies and assess their applicability to life sciences challenges.

- Drive proof-of-concepts (POCs) and pilots to validate new ideas and approaches.

Required Qualifications :

Experience & Technical Skills :

- 10+ years of experience in AI/ML, data science, or advanced analytics roles.

- Proven experience designing and deploying enterprise-scale AI/ML solutions.

- Strong proficiency in Python and R for data analysis and model development.

- Deep understanding of AI/ML algorithms and techniques, including :

- Supervised and unsupervised learning

- Deep learning frameworks (TensorFlow, PyTorch, Keras)

- NLP techniques (transformers, embeddings, LLMs)

- Strong experience with cloud platforms : AWS, Azure, or GCP.