AI Engineer - Fullstack - 12 LPA (3+ Years)
Jumbo Consulting
Bengaluru, Karnataka, India
Experience: 2–5 Years
Location: Bangalore
Compensation: Up to ₹12 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, optimisation, 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 optimise 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
- 2–5 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.