AI Engineer

About the Role and Company

Join a fast-growing AI-led health technology and biotechnology firm dedicated to revolutionizing drug discovery through advanced artificial intelligence. Our platform integrates AI, machine learning, predictive analytics, and comprehensive biological and multi-omics data to assist researchers and life sciences companies in identifying promising drugs, forecasting their efficacy and safety, and accelerating therapeutic development while cutting costs.

Role Overview

As an AI Engineer, you will collaborate intensely with AI/ML experts and scientific teams to conceive, build, and deploy machine learning solutions targeting healthcare and drug discovery challenges. Your involvement spans the entire AI development cycle — from processing data, crafting models, experimenting, validating, optimizing, to deploying in production environments.

Key Responsibilities

• Create and implement machine learning and AI models for applications in healthcare and life sciences.
• Handle extensive structured, unstructured, and biological/multi-omics datasets.
• Develop predictive models focused on drug activity, effectiveness, safety, and biological outcomes.
• Build, fine-tune, and streamline pipelines for data preprocessing, feature engineering, and model training.
• Experiment with cutting-edge deep learning, natural language processing, and generative AI methods as relevant.
• Assess model performance using proper statistical and machine learning metrics.
• Enhance model precision, scalability, robustness, and inference efficiency.
• Work alongside data scientists, computational biologists, and domain specialists to translate scientific questions into ML solutions.
• Develop APIs and production-ready services surrounding AI/ML models.
• Support MLOps activities, including model version control, monitoring, testing, and deployment.
• Keep abreast of the latest innovations in AI/ML, deep learning, and healthcare AI applications.

Required Qualifications and Skills

• Between 2 and 5 years of practical experience in AI/ML engineering or machine learning roles.
• Advanced proficiency in Python programming.
• Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Comprehensive knowledge of machine learning algorithms, deep learning techniques, model evaluation and tuning, data preprocessing, feature engineering, statistics, and probability.
• Experience working with SQL and developing data-processing pipelines.
• Proven capability in building and deploying machine learning models into production environments.
• Familiarity with REST APIs, version control with Git, and cloud computing platforms.
• Excellent analytical and problem-solving abilities.

Preferred but Not Mandatory

• Exposure to generative AI and large language models (LLMs).
• Knowledge of NLP and transformer-based architectures.
• Background or experience in healthcare, biotechnology, pharmaceuticals, or computational biology.
• Experience handling biological, genomic, or multi-omics datasets.
• Proficiency with cloud providers such as AWS, Google Cloud, or Azure.
• Practical use of Docker, Kubernetes, or other container orchestration technologies.
• Understanding of MLOps practices and large-scale model deployment.

What You Can Expect

• Opportunity to apply state-of-the-art AI methods to impactful healthcare and drug discovery problems.
• High degree of ownership and direct involvement with emerging AI innovations.
• Fully remote working arrangement.
• Chance to collaborate closely with AI specialists, engineers, and scientific experts.
• Competitive salary package up to 20 lakh rupees per annum.

Ideal Candidate Traits

• Technically strong with the ability to deliver end-to-end AI solutions.
• Curious and enthusiastic about expanding AI applications beyond conventional software domains.
• Motivated by working with large and complex datasets with scientific contexts.
• Comfortable thriving in a fast-paced startup atmosphere.
• Passionate about leveraging AI to make a significant positive impact in healthcare.