What is the role about?

We are looking for an experienced Machine Learning Lead to drive end-to-end AI/ML initiatives, from problem definition to production deployment. This role combines technical leadership, architecture design, and hands-on model development, ensuring scalable and business-aligned ML solutions. You will lead a team of data scientists and engineers while collaborating with cross-functional teams to build impactful AI-driven products.

Key Responsibilities :

Technical Leadership :

- Lead the design and development of scalable machine learning solutions
- Define ML architecture, model selection, and feature engineering strategies
- Guide teams on best practices in model development, evaluation, and deployment
- Review code, models, and pipelines to ensure high-quality delivery

Model Development &

- Optimization :
- Build and deploy models for :
- Customer churn prediction
- Recommendation systems
- Demand forecasting
- Customer segmentation
- Optimize models for :
- Accuracy
- Performance
- Scalability

Data &

- Feature Engineering :
- Design robust data pipelines for :
- Data ingestion
- Feature engineering
- Data validation
- Handle large-scale structured and unstructured datasets

MLOps &

- Deployment :
- Lead production deployment using :
- AWS SageMaker / Lambda / APIs
- Docker, CI/CD pipelines
- Implement :
- Model monitoring
- Retraining pipelines
- Versioning and experiment tracking (MLflow)

Business Collaboration :

- Translate business problems into ML solutions
- Work with stakeholders to define KPIs and success metrics




- Drive data-driven decision-making across teams

Team Management :

- Mentor junior and mid-level data scientists
- Conduct technical reviews and knowledge-sharing sessions
- Build a high-performance ML team

Must-Have Criteria :

- 6 years of experience in AI/ML or Data Science
- Solid expertise in :

1.

Machine

Learning (supervised & unsupervised)

- Feature engineering & model tuning/optimization
- Proficiency in :
- Python (NumPy, Pandas, Scikit-learn)

2.

At least one : TensorFlow / PyTorch

- Strong understanding of :
- Probability &
- Statistics

2.

Linear

Algebra

3.

Data Mining

Concepts and Problem understanding and Solving Skills

- Experience with :
- Large-scale data processing
- SQL and databases (PostgreSQL, MySQL, MongoDB)
- Hands-on experience in deploying ML models to production
- Strong debugging and optimization skills

Preferred Skills :

Experience with a wide range of machine learning use cases, including but not limited to :

- Recommendation systems
- Time series forecasting
- Customer analytics (churn prediction, segmentation, CLV)
- Classification and regression problems
- Anomaly detection and fraud detection
- NLP use cases (text classification, information extraction)




- Demand forecasting and inventory optimization
- Personalization and targeting models
- Ability to quickly understand and adapt ML solutions to new business problems across domains
- MLOps tools :
- MLflow, Docker, Kubernetes
- Cloud platforms :
- AWS (SageMaker, S3, Lambda)
- Experience in building :
- REST APIs for ML inference
- Knowledge of :
- Data visualization (Power BI, matplotlib, seaborn)

Leadership &

- Soft Skills :
- Strong problem-solving mindset
- Ability to lead and mentor teams
- Excellent communication with both technical and business stakeholders
- Experience handling end-to-end project ownership

Preferred Qualifications :

- Bachelors/Masters degree in :

1.

Computer

Science

- Data Science
- Mathematics
- Statistics
- Engineering
- Relevant certifications in AI/ML or Cloud (AWS/Azure/GCP)

Good to Have :

- Experience in GenAI / LLM-based systems
- Knowledge of :
- RAG pipelines
- Prompt engineering
- Experience in building and deploying ML solutions across multiple industry domains, including but not limited to :
- Retail (recommendation systems, demand forecasting, customer segmentation)
- Healthcare (clinical data analysis, predictive diagnostics, operational optimization)

3.

Financial

Services (fraud detection, risk modeling, credit scoring)

- E-commerce and Digital Platforms
- Logistics and Supply Chain
- Telecom and Customer Engagement platforms
- Ability to understand domain-specific challenges and translate them into scalable, data-driven ML solution

📌 Machine Learning Lead (India)
🏢 Ajni Consulting
📍 India