Introduction The founding of Metropolitan dates to as early as 1898 and Momentum traces its roots to being established in 1966. Momentum Group was formed from the merger of Metropolitan and Momentum, two sizeable and diverse insurance-based financial services companies in South Africa and was listed on the Johannesburg Stock Exchange on 1 December 2010.

In order to grow its international footprint and diversify its revenue streams, Momentum Group actively pursues financially viable opportunities across the world. Aditya Birla Health Insurance Company Limited, a joint venture with Aditya Birla Capital Limited, was incorporated in 2015 and was our first expansion into India.

Having experienced India first-hand as a hub of both talent and opportunity, we set up Momentum Services in 2017, a wholly-owned Mumbai-based global in-house centre to leverage IT, ITES and Business support services to all our businesses worldwide.

Role Purpose The Machine Learning Engineer is responsible for designing, developing, deploying,

and maintaining machine learning models and AI-driven solutions that solve complex business problems. The role involves working closely with data scientists, software engineers, and business stakeholders to transform data into scalable and productionready intelligent systems.

Duties & Responsibilities

KEY ACCOUNTABILITIES/KRAs/KPIs

- Design, build, train, validate, and deploy machine learning models to address business challenges.
- Collaborate with business stakeholders to understand requirements and translate them into AI/ML solutions.
- Perform data collection, cleansing, preprocessing, and feature engineering activities.




- Evaluate model performance using appropriate metrics and optimize models for accuracy and scalability.
- Develop and maintain data pipelines to support machine learning workflows.
- Implement MLOps best practices for model deployment, version control,

monitoring, and retraining.

- Work closely with engineering teams to integrate ML solutions into production systems.
- Conduct exploratory data analysis and derive meaningful insights from large datasets.
- Prepare technical documentation, model reports, and implementation guides.
- Ensure adherence to security, governance, and compliance standards in AI implementations.
- Support production issues and continuously improve deployed machine learning solutions.
- Participate in sprint planning, code reviews, and technical discussions.
- Develop and optimize APIs and services for serving machine learning models in production environments.
- Monitor model performance, drift, and data quality, ensuring timely retraining and enhancements.
- Build scalable and reusable ML solutions that can be leveraged across multiple business use cases.
- Conduct proof of concepts (POCs) and feasibility assessments for new AI/ML initiatives.

Requirements

- 5+ yrs of hands-on experience in developing, training, and deploying Machine

Learning models in production environments.

- Strong proficiency in Python and Machine Learning frameworks such as Scikitlearn, TensorFlow, PyTorch, or Keras.




- Experience in data preprocessing, feature engineering, model evaluation, and optimization using structured and unstructured datasets.
- Exposure to cloud-based ML solutions (Azure, AWS, or GCP), MLOps practices,

CI/CD pipelines, and model monitoring.

Competencies

Mandatory Skills

- Strong proficiency in Python programming.
- Experience with Machine Learning frameworks such as

Scikit-learn, TensorFlow, PyTorch, or Keras.

- Valuable understanding of Machine Learning algorithms,

statistics, and probability concepts.

- Experience with data preprocessing, feature engineering,

and model validation techniques.

- Strong knowledge of SQL and database systems.
- Experience with cloud platforms such as Azure ML, AWS

SageMaker, or Google Vertex AI.

- Understanding of MLOps, model deployment, monitoring,

and automation.

- Experience with Git, Docker, and CI/CD pipelines.
- Knowledge of NLP, Deep Learning, Computer Vision, or

Generative AI concepts.

- Familiarity with API development and microservices architecture.
- Strong debugging, analytical, and optimization skills.

Preferred Skills

- Experience with LLMs, RAG architectures, LangChain,

Semantic Kernel, or AI Agents.

- Experience in Generative AI product development.

Behavioral Competencies

- Strong analytical and critical-thinking skills.
- Excellent verbal and written communication skills.
- Proactive and self-motivated individual.
- Strong ownership and accountability mindset.
- Effective collaboration and teamwork abilities.
- Continuous learning attitude and innovation mindset.
- Ability to manage priorities and deliver results within timelines.

📌 Machine Learning Engineer (Navi Mumbai)
🏢 Momentum Group
📍 Navi Mumbai