Machine Learning Engineer — Spatial Intelligence
AI and Machine Learning
Bengaluru
3-5 Years
Full-time
On-site
Client Project Opportunity
We are looking for a technically strong Machine Learning Engineer who has worked across a wide range of machine learning problems rather than one narrow specialization. You will own machine learning models end to end, including framing business problems, cleaning complex sensor data, selecting appropriate algorithms, and deploying models to production. This is a hands-on role involving extensive Python development and live production deployments.
About the Role
We are looking for a technically strong Machine Learning Engineer who has worked across a wide range of machine learning problems rather than one narrow specialization.
You will own machine learning models end to end, including framing business problems, cleaning complex sensor data, selecting appropriate algorithms, and deploying models to production. This is a hands-on role involving extensive Python development and live production deployments.
Key Responsibilities
- Translate ambiguous business requirements into clearly defined machine learning problems.
- Build and evaluate models for classification, forecasting, clustering, anomaly detection and time-series analysis.
- Clean, transform and prepare noisy real-world data collected from sensors and video systems.
- Create visualizations that clearly communicate data quality, patterns and model behavior.
- Build appropriate features and select algorithms based on the characteristics of each problem.
- Deploy machine learning models into production environments.
- Monitor production model performance and identify degradation or data-quality problems.
- Retrain and improve models based on production data and performance metrics.
- Collaborate with product, engineering and business teams to deliver production-ready machine learning solutions.
Must-Have Skills & Experience
- 3–5 years of experience building and deploying machine learning models.
- Strong Python programming skills.
- Hands-on experience with NumPy, pandas and scikit-learn.
- Experience with PyTorch or TensorFlow.
- Strong understanding of machine learning fundamentals, including probability, statistics, linear algebra and optimization.
- Ability to explain why an algorithm works, justify its selection and identify where it may fail.
- Strong data-cleaning, feature-engineering and data-visualization skills.
- Hands-on experience with MongoDB, including aggregation pipelines, indexing and querying large collections.
- Working experience with Kafka and streaming data pipelines.
- Practical MLOps experience covering Docker, CI/CD, experiment tracking and model monitoring.
- Strong problem-solving and debugging skills with the ability to work independently.
- Experience taking machine learning models from initial problem definition through production deployment.
Good to Have
- Experience with manufacturing production lines, shop-floor systems or plant analytics.
- Knowledge of Overall Equipment Effectiveness, yield, throughput or output prediction.
- Experience with predictive maintenance, equipment alarms or Statistical Process Control.
- Exposure to industrial data sources such as MES, SCADA, PLC systems or data historians.
- Experience with agentic workflows and multi-agent systems.
- Experience with workflow-orchestration tools.
- Experience with Large Language Models and Retrieval-Augmented Generation pipelines.
- Computer vision experience.
- Experience with cloud machine learning platforms on AWS, Google Cloud or Microsoft Azure.
- Experience with Kubernetes.
- Experience deploying machine learning models to edge environments.
Role Details
- Experience - 3-5 Years
- Location - Bengaluru, India
- Work Mode - On-site
- Employment - Full-time
- Deployment - Client Project
- Domain - Machine Learning / Spatial Intelligence / Industrial Analytics
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