AI/ML Engineer/Manager

AI/ML Engineer/Manager:

Location – Pune

Experience: 6+ years

Notice period – Immediate to 30 days. 

Key Responsibilities:

• Lead the development of

  machine learning PoCs and demos

  using structured/tabular data for use cases such as forecasting, risk scoring, churn prediction, and optimization. 
• Collaborate with sales engineering teams to understand client needs and

  present ML solutions

  during pre-sales calls and technical workshops. 
• Build ML workflows using tools such as

  SageMaker, Azure ML, or Databricks ML

  and manage training, tuning, evaluation, and model packaging. 
• Apply

  supervised, unsupervised, and semi-supervised techniques

  such as XGBoost, CatBoost, k-Means, PCA, time-series models, and more. 
• Work with data engineering teams to define

  data ingestion, preprocessing, and feature engineering

  pipelines using Python, Spark, and cloud-native tools. 
• Package and document ML assets so they can be scaled or transitioned into delivery teams post-demo. 
• Stay current with best practices in

  ML explainability

  ,

  model performance monitoring

  , and

  MLOps

  practices. 
• Participate in internal knowledge sharing, tooling evaluation, and continuous improvement of lab processes. 

Qualifications:

• 8+ years

  of experience developing and deploying classical machine learning models in production or PoC environments. 
• Strong hands-on experience with

  Python

  ,

  pandas

  ,

  scikit-learn

  , and ML libraries such as

  XGBoost, CatBoost

  , LightGBM, etc. 
• Familiarity with

  cloud-based ML environments

  such as

  AWS SageMaker

  ,

  Azure ML

  , or

  Databricks

  . 
• Solid understanding of

  feature engineering, model tuning, cross-validation, and error analysis

  . 
• Experience with

  unsupervised learning

  , clustering, anomaly detection, and dimensionality reduction techniques. 
• Comfortable presenting models and insights to

  technical and non-technical stakeholders

  during pre-sales engagements. 
• Working knowledge of

  MLOps concepts

  , including model versioning, deployment automation, and drift detection. 

Interested candidates shall apply or share resumes at kanika.garg@austere.co.in.