Lead I Senior Machine Learning Engineer

Bangalore - India

Monthly Salary: INR 2300000 - 3500000

Experience Required: 8-12years

Posted on: 27 days ago

Vacancies: 1 Vacancy

Job Summary

Senior Machine Learning Engineer

Experience: 8 years

Location: Bengaluru (Hybrid)

Responsibilities:

Design develop and deploy machine learning models and algorithms for production use with clear SLAs.
Build and maintain scalable reliable data pipelines (batch and streaming) for training and inference.
Perform exploratory data analysis to uncover insights define hypotheses and guide feature design.
Develop robust feature engineering processes; manage feature definitions lineage and reuse across teams.
Implement model serving as APIs/services (REST/gRPC) using Flask/FastAPI/Django with proper versioning and rollback.
Establish CI/CD for ML (testing packaging model artifacts) with automated deployments and canary/blue-green strategies.
Set up experiment tracking model registry and reproducible training workflows.
Define and monitor offline/online metrics.
Implement observability across data models and services (latency throughput drift data quality cost).
Collaborate with product data and platform teams to translate requirements into technical designs and roadmaps.
Write clear documentation and participate in code reviews and mentoring.
Participate in incident response and on-call rotations for ML services.

Requirements

Requirements:

Minimum of 8 years of experience in machine learning data analysis and feature engineering with production ownership.
Strong proficiency in Python and its libraries (NumPy pandas scikit-learn) .
Experience with one or more web frameworks such as Flask FastAPI or Django to build production-grade APIs.
Solid understanding of ML algorithms evaluation techniques experiment design and statistical testing.
Proficiency in SQL and data modeling; experience with large datasets and performance optimization.
Hands-on experience with data processing frameworks (e.g. Spark/Beam/Flink) and streaming platforms (e.g. Kafka/Kinesis).
Strong software engineering skills: modular design type hints unit/integration testing (pytest) logging and profiling.
Experience with containers and orchestration (Docker Kubernetes) and infrastructure-as-code concepts.
Familiarity with CI/CD tools (e.g. GitHub Actions/GitLab/Jenkins) for automating ML builds and releases.
Monitoring/observability experience (e.g. Prometheus/Grafana/OpenTelemetry) and data quality checks/drift detection.
Excellent communication skills to effectively convey technical concepts to non-technical stakeholders and drive alignment.

Good to have:

Experience with cloud platforms (AWS preferred) and common services (e.g. S3 ECR ECS/EKS Lambda/Batch IAM).
Experience with MLOps practices and tools (feature stores data/version management like DVC/LakeFS workflow orchestration like Airflow/Dagster).
Experience with Natural Language Processing (NLP) computer vision recommendation/ranking or time-series forecasting.
Familiarity with dashboarding/visualization for analysis and monitoring (Matplotlib Plotly Grafana Streamlit).

Required Skills:

Minimum of 7 years of experience in machine learning data analysis and feature engineering with production ownership. Strong proficiency in Python and its libraries (NumPy pandas scikit-learn) . Experience with one or more web frameworks such as Flask FastAPI or Django to build production-grade APIs. Solid understanding of ML algorithms evaluation techniques experiment design and statistical testing. Proficiency in SQL and data modeling; experience with large datasets and performance optimization. Hands-on experience with data processing frameworks (e.g. Spark/Beam/Flink) and streaming platforms (e.g. Kafka/Kinesis). Strong software engineering skills: modular design type hints unit/integration testing (pytest) logging and profiling. Experience with containers and orchestration (Docker Kubernetes) and infrastructure-as-code concepts. Familiarity with CI/CD tools (e.g. GitHub Actions/GitLab/Jenkins) for automating ML builds and releases. Monitoring/observability experience (e.g. Prometheus/Grafana/OpenTelemetry) and data quality checks/drift detection. Excellent communication skills to effectively convey technical concepts to non-technical stakeholders and drive alignment

Senior Machine Learning Engineer Experience: 8 years Location: Bengaluru (Hybrid) Responsibilities: Design develop and deploy machine learning models and algorithms for production use with clear SLAs. Build and maintain scalable reliable data pipelines (batch and streaming) for training and inferenc...