Lead ML Engineer

1 week ago

Bengaluru, India Senzcraft Full time

About Senzcraft:Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies.We have a suite of SaaS products and services, partnering with automation product companies.Please visit our website - for more detailsOur AI Operations SaaS platform – on linkedin -> is awarded by Analytics India Magazine in it’s report “State of AI in India” as a “Niche AI startup”. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.About the Role (Lead ML Engineer):Location: Bangalore – HybridExperience: We have multiple roles open (6-12 years)Employment Type: Full-timeJob Description:We are looking for a Lead ML Engineer to design, build, and scale machine learning solutions. The ideal candidate will have strong hands-on experience with ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers) and a proven track record in ML Ops, model monitoring, and lifecycle management.This role will also drive innovation in big data processing using Spark, Databricks, and Delta Live Tables, with a focus on cloud deployment on AWS.Key Responsibilities- Design, build, and deploy scalable ML systems leveraging TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers for supply chain and logistics–specific use cases (e.g., demand forecasting, route optimization, inventory management).- Define and implement ML Ops best practices — CI/CD pipelines, model versioning, monitoring, and retraining workflows.- Develop robust data pipelines and scalable solutions using Spark, Databricks, and Delta Live Tables.- Collaborate with data scientists and software engineers to bring models from research to production.- Optimize model performance, latency, and resource utilization in AWS cloud environments.- Ensure end-to-end model lifecycle management, including governance, observability, and retraining strategies.Mandatory Skills- Strong experience with TensorFlow, PyTorch, scikit-learn, and Hugging Face Transformers.- Deep understanding of ML Ops practices — deployment, monitoring, and lifecycle management.- Expertise in big data frameworks — Spark, Databricks, Delta Live Tables.- Hands-on experience with AWS ML and data services (SageMaker, Lambda, EMR, S3, etc.).- Proficiency in Python, version control (Git), and CI/CD tools.Good to Have- Exposure to containerization (Docker, Kubernetes) and infrastructure as code (Terraform).- Experience with data streaming (Kafka, Kinesis) or feature store frameworks.- Knowledge of LLM optimization or deployment in production environments.Education- Bachelor’s or Master’s in Computer Science, Data Engineering, or a related field.

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