Data Scientist

Monaire Inc.; Pune District; Remote; INR 2,800,000 - 4,200,000; Full time

Benefits offered by this job

Health insurance

Remote-first culture

Job summary

Monaire is building the infrastructure layer for intelligent HVAC systems in Pune. You will develop production-grade ML systems that drive energy efficiency, predictive maintenance, and operational intelligence for HVAC/R platforms.

You will collaborate with backend engineers, PMs, and domain experts to translate sensor data into reliable models powering customer-facing features and internal decision-making.

Qualifications

• 2+ years hands-on data science/ML experience.
• Deep learning: TensorFlow, Keras, or PyTorch.
• MongoDB: Query optimization, indexing, aggregation pipelines.
• Batch processing: Parallel processing (multiprocessing/async).
• Time-series data, anomaly detection, statistical modeling.
• Strong CS fundamentals and debugging skills.

Responsibilities

• Scale ML systems for growth—optimize batch processing, queries, and model inference.
• Design ML models for time-series data and anomaly detection.
• Optimize production systems: <3s response times, cost reduction, high uptime.

Skills

Data science

Deep learning

Time-series analysis

Anomaly detection

Statistical modeling

CS fundamentals

MLOps

NLP/LLM

AWS (Lambda/S3)

Education

Bachelor's/Master's/PhD in CS/IT/Applied Math/Statistics

Tools

MongoDB

Job description

Monaire is building the infrastructure layer for intelligent commercial HVAC. We combine on-device sensors, smart thermostats, and machine-learning systems to automate control, surface real operational insight, and materially reduce energy waste at scale.

This is not offline modeling or notebook ML. Models run in production, interact with physical systems, and must be observable, debuggable, and correct. The platform spans edge devices, cloud services, streaming pipelines, control logic, and ML inference.

Engineers here work on:

Data ingestion and streaming at scale from heterogeneous hardware

Low-latency decision pipelines and control loops

ML systems that survive missing data, drift, and adversarial real-world conditions

Infrastructure for model deployment, monitoring, and rollback

Apps and services that customers depend on to run their buildings every day

The market is large, broken, and technically underserved. We’re scaling the system and need engineers who care about correctness, performance, and ownership — people who want to build infrastructure that actually controls the physical world, not just dashboards that look good in demos.

Role Overview

As a Data Scientist / Senior Data Scientist , you will play a critical role in building production-grade ML systems that drive real-world outcomes—energy efficiency, predictive maintenance, anomaly detection, and operational intelligence for HVAC/R systems.

You will work closely with backend engineers, product managers, and domain experts to translate raw sensor data into reliable models that power customer-facing features and internal decision-making.

This role requires someone who can think long-term architecturally , while delivering short-term, measurable impact in a fast-moving startup environment.

What You'll Do:

• Scale ML systems for 5X growth—optimize batch processing, database queries, and model inference
• Design ML models for time-series data, anomaly detection, and predictive maintenance
• Optimize production systems: <3s response times, 30% cost reduction, 99.9% uptime
• Database optimization (MongoDB): indexes, connection pooling, 3-5X performance improvement
• Batch processing: parallel processing, async operations, memory management
• Model optimization: <500ms inference latency, caching strategies
• NLP & LLM: enhance conversational AI bots with intelligent query generation
• Build monitoring systems: real-time dashboards, SLA tracking, automated scaling

Requirements

Must-Have Skills

• 2+ years hands-on data science/ML experience
• Deep learning: TensorFlow, Keras, or PyTorch
• MongoDB: Query optimization, indexing, aggregation pipelines
• Batch processing: Parallel processing (multiprocessing/async)
• Time-series data, anomaly detection, statistical modeling
• Strong CS fundamentals and debugging skills

Nice-to-Have Skills

• MLOps tools, Lambda optimization, caching (Redis/ElastiCache)
• NLP/LLM: Prompt engineering, conversational AI
• AWS: Lambda, S3, CloudWatch, ElastiCache/Redis

Qualifications

• Bachelor's/Master's/PhD in CS, IT, Applied Math, Statistics, or related field
• Competitive salary + equity with meaningful ownership
• Comprehensive health insurance (self, spouse, children, and parents)
• Remote-first, flexible work culture
• Opportunity to work on high-impact systems with climate and sustainability impact
• Strong emphasis on engineering excellence, ownership, and growth
• Collaborative, inclusive, and low-ego team culture