AI Engineer (10 LPA) (3+ Years)

Experience: 2–5 Years
Location: Bangalore
Compensation: Up to ₹10 LPA
Employment Type: Full-time
About the Company
We are a rapidly growing AI-driven health-tech / biotech company building advanced artificial intelligence systems to transform drug discovery and development.
Role Overview
As an AI Engineer, you will work closely with AI/ML and scientific teams to design, develop and deploy machine-learning solutions for healthcare and drug-discovery applications.
You will be involved across the AI lifecycle — from data processing and model development to experimentation, evaluation, optimization and production deployment.
Key Responsibilities
Design, develop and deploy machine learning and AI models for healthcare and life-sciences applications.
Work with large-scale structured, unstructured and biological/multi-omics datasets.
Develop predictive models for areas such as drug activity, efficacy, safety and biological outcomes.
Build and optimize data preprocessing, feature engineering and model-training pipelines.
Experiment with modern deep learning, NLP and generative AI techniques where appropriate.
Evaluate model performance using appropriate statistical and ML metrics.
Improve model accuracy, scalability, robustness and inference performance.
Collaborate with data scientists, computational biologists and domain experts to translate scientific problems into ML solutions.
Develop APIs and production-ready services around AI/ML models.
Contribute to MLOps practices including model versioning, monitoring, testing and deployment.
Stay current with advances in AI/ML, deep learning and AI applications in healthcare.
Required Skills
3–5 years of hands-on experience in AI/ML engineering or machine learning.
Strong proficiency in Python.
Experience with ML frameworks such as PyTorch, TensorFlow or scikit-learn.
Strong understanding of:
Machine learning algorithms
Deep learning
Model evaluation and optimization
Data preprocessing and feature engineering
Statistics and probability
Experience working with SQL and data-processing pipelines.
Experience building and deploying ML models in production.
Familiarity with REST APIs, Git and cloud environments.
Strong problem-solving and analytical skills.
Good to Have
Experience with Generative AI / LLMs.
Experience with NLP or transformer architectures.
Exposure to healthcare, biotechnology, pharmaceuticals or computational biology.
Experience working with multi-omics, genomic or biological datasets.
Knowledge of cloud platforms such as AWS, GCP or Azure.
Experience with Docker, Kubernetes or other containerization technologies.
Familiarity with MLOps and model deployment at scale.

Work arrangement
No