Back
Remote, popular ML role at mid experience level with broad skills amplifies applicant competition.
Core ML engineering skills are transferable, though insurance domain knowledge moderately matters.
Explicit 2-4 year requirement plus mandatory Python and ML stack increases filtering strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy machine learning solutions tailored for the life insurance lifecycle to support Max Life’s business operations.
Work extensively with large data sets for data discovery, hypothesis validation, model development, and ongoing performance monitoring of AI models.
Apply new AI techniques and present analytical insights and model outcomes to key business stakeholders.
2-4 years of hands-on experience in building and deploying machine learning models, including supervised and unsupervised algorithms (Logistic Regression, kNN, KMeans, Random Forest, SVM, XGBoost, Naïve Bayes, Time series forecasting).
Master's degree (MTech/ME/MSc) in Computer Science, IT, or quantitative disciplines from Tier 1 or Tier 2 institutes (IIT, IIIT, NIT, BITS, or equivalent).
Mandatory excellent programming skills in Python; experience with PySpark, Scikit-learn, TensorFlow required.
Experience working with large data sets and integrating AI/ML solutions into technology systems. Work Experience Required: 2-4 years.
Strong mathematical and algorithmic foundation with proven project experience in AI/ML technology development and deployment within data-intensive environments.
Able to handle fast-paced work with minimal supervision, comfortable working in lean teams and ownership of end-to-end ML model lifecycle.
Experience or willingness to engage with cloud infrastructure and high-performance computing resources (GPU/TPU) is a plus but not mandatory.