Machine Learning Engineer

eInfochips (An Arrow Company); Ahmedabad District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

eInfochips (An Arrow Company) seeks a seasoned ML/AI engineer to design and deploy scalable ML pipelines and governance frameworks. You will work with TensorFlow, PyTorch, Spark, and MLflow to deliver end-to-end models from data prep to evaluation.

You will build dashboards for model monitoring and KPIs, mentor juniors, and stay current with Generative AI trends while applying software engineering practices for reusable ML code.

Qualifications

• Deep understanding of supervised, unsupervised, and reinforcement learning, model evaluation, and feature engineering.
• Hands-on experience with TensorFlow, PyTorch, Keras; CNNs and RNNs.
• Expert in Python with NumPy, Pandas, scikit-learn; R exposure acceptable.
• Experience with Spark, Hadoop, Kafka; cloud ML services and MLOps exposure.
• Strong knowledge of SQL, NoSQL and data modeling.
• Hands-on experience with model drift detection, monitoring, and alerts.
• Experience implementing data governance, lineage tracking, metadata management, and compliance.
• Architect scalable MLOps pipelines using Azure ML, MLflow, Databricks Asset Bundles, and CI/CD/CT.

Responsibilities

• Architect scalable MLOps pipelines using Azure ML, MLflow, Databricks Asset Bundles (DAB), and CI/CD/CT.
• Build Power BI dashboards for monitoring models and reporting business KPIs.
• Mentor juniors, review code, and conduct technical knowledge-sharing sessions.

Skills

Machine Learning

Deep Learning

Python

Spark

MLOps

SQL

NoSQL

Model Monitoring

Data Governance

CI/CD

Azure

Databricks

Tools

TensorFlow

PyTorch

Keras

MLflow

Spark

Databricks

Hadoop

Kafka

Azure ML

DAB

Job description

• Machine Learning: Deep understanding of supervised, unsupervised, and reinforcement learning, model evaluation, and feature engineering.
• Deep Learning: Proficiency with TensorFlow, PyTorch, Keras; hands-on with CNNs, RNNs.
• Programming: Expert in Python (NumPy, Pandas, scikit-learn, etc.); R exposure acceptable.
• Big Data Technologies: Practical experience with Spark (Databricks preferred); familiarity with Hadoop/Kafka.
• Cloud Platforms: Azure or AWS or GCP (ML services, data storage, compute), with strong MLOps exposure.
• Data Warehousing & Databases: Strong SQL, NoSQL, and data modeling.
• Drift Detection & Monitoring: Hands-on experience with model drift detection, monitoring, and automated alerts.
• Data Governance: Practical experience implementing governance frameworks, lineage tracking, metadata management, and compliance.
• Architect scalable MLOps pipelines using Azure ML, MLflow, Databricks Asset Bundles (DAB), and CI/CD/CT

Good-to-Have.

• Build Power BI dashboards for monitoring models and reporting business KPIs.
• Strong grounding in statistics, hypothesis testing, and data interpretation.
• Apply software engineering principles for reusable, testable, and maintainable ML code.
• Stay up to date with Generative AI, Agentic AI, and LLMs and assess practical adoption.
• Mentor juniors, review code, and conduct technical knowledge-sharing sessions.
• Certification: Microsoft Certified: Azure Data Scientist Associate (nice to have).