AI/ML (Java, APIs, Microservices)

4 days ago

Navi Mumbai, Maharashtra, India TransformHub Full time ₹ 12,00,000 - ₹ 36,00,000 per year

About the Role:

We are seeking a Senior ML Platform Engineer to architect and build real-time AI systems that process streaming financial data. You'll be responsible for developing scalable machine learning infrastructure that powers intelligent financial recommendations, personalized user experiences, and real-time analytics.

Location: Navi Mumbai

Experience: 3-8 years

Key Responsibilities

Real-Time Data Processing

  • Design and implement
    Apache Kafka-based streaming pipelines

for high-volume financial data
- Build robust
event-driven architectures

to process real-time market data and user interactions
- Integrate with
microservices

and external financial APIs for seamless data flow
- Implement
stream processing logic

using Kafka Streams or Apache Flink

AI/ML Infrastructure

  • Deploy and maintain
    machine learning models

in production environments
- Build
real-time inference pipelines

for AI-powered financial recommendations
- Implement
MLOps practices

including model versioning, monitoring, and automated retraining
- Optimize
model serving infrastructure

for low-latency predictions

Platform Development

  • Architect
    scalable data platforms

on cloud infrastructure (Azure/AWS)
- Develop
APIs and microservices

for ML model integration
- Implement
monitoring and alerting systems

for data quality and model performance
- Ensure
security and compliance

with financial industry standards

Cross-functional Collaboration

  • Work closely with
    data science teams

to productionize ML models
- Collaborate with
backend engineers

on system integration
- Partner with
product teams

to understand business requirements
- Contribute to technical decision-making

Technical Expertise

  • 3+ years

of experience in building production ML systems
- Strong expertise in Apache Kafka

and event streaming architectures
- Proficiency in Python and Java

for ML and streaming applications
- Experience with ML frameworks

(TensorFlow, PyTorch, Scikit-learn)
- Cloud platforms knowledge

(Azure, AWS, or GCP)
- Database technologies

(PostgreSQL, MongoDB, Redis)
- Containerization and orchestration

(Docker, Kubernetes)

Engineering Practices

  • Strong software engineering principles

and clean coding practices
- Experience with CI/CD pipelines

and DevOps practices
- API design and microservices architecture
- Performance optimization

for high-throughput systems
- Version control

(Git) and collaborative development

Preferred Qualifications

Advanced AI/ML Skills

  • Experience with
    Large Language Models (LLMs)

and modern AI architectures
- Knowledge of
recommendation systems

and personalization engines
- Vector databases

and similarity search systems (Pinecone, Weaviate)
- Real-time feature engineering

and online learning systems

Streaming & Infrastructure

  • Apache Flink

or advanced Kafka ecosystem tools (Connect, Schema Registry)
- Time-series databases

(InfluxDB, TimescaleDB) for financial data
- Message queue systems

beyond Kafka (RabbitMQ, Apache Pulsar)
- Model optimization

techniques for production deployment

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