Machine Learning Engineer

Location:Indore (On-site only)

About Us

At Neural Nurture, we are committed to advancing the frontiers of Artificial Intelligence and Machine Learning. Our research lab focuses on solving some of the most exciting and challenging problems in Machine Learning, Natural Language Processing, and Computer Vision.

Role Overview

As an ML Engineer, you will bridge the gap between research and production - building,optimizing, and deploying ML systems that power real-world products.Youllwork closely with Applied Scientists and product teams to take models from prototype to scalable, reliable services.

Areas of focus could be one or more of the following:

• ML Systems & Infrastructure:Building robust training and inference pipelines, model serving, and monitoring systems.
• NLP Engineering:Deploying andoptimizinglanguage models for tasks such as conversational AI, information extraction, and search.
• Computer Vision Engineering:Building production-grade vision pipelines for image/video analysis and understanding.
• MLOps:EstablishingCI/CD for ML, experiment tracking, model versioning, and automated retraining workflows.

Responsibilities

• Design, build, andmaintainend-to-end ML pipelines - from data ingestion and feature engineering to model training, evaluation, and deployment.
• Optimizemodels for latency, throughput, and cost in production environments.
• Collaborate with Applied Scientists to translate research prototypes into production-ready systems.
• Build andmaintainML infrastructure including experiment tracking, model registries, and monitoring/alerting for model performance drift.
• Develop APIs and services to expose ML capabilities to downstream applications.
• Write clean, well-tested, and documented code following engineering best practices.
• Troubleshoot and debug issues across the full ML stack - data, training, and serving.

Qualifications

• Bachelors orMasters in Computer Science, Machine Learning, ora related field.
• Strong programming skills in Python.
• Experience building and deploying ML models in production environments.
• Proficiencywith Deep Learning frameworks (PyTorchpreferred).
• Solid understanding of ML fundamentals - training, evaluation, overfitting, data leakage, etc.
• Experience with ML pipeline/orchestration tools (e.g.,Metaflow, Airflow, Kubeflow).
• Familiarity with REST APIs, containerization (Docker), and cloud platforms (AWS/GCP).
• Strong software engineering practices - version control (Git), testing, code review.

Preferred Qualifications

• Experience with NLP systems (Transformers, LLM serving, RAG pipelines) or CV systems in production.
• Familiarity with model optimization techniques - quantization, distillation, ONNX,TensorRT.
• Experience with experiment tracking tools (MLflow, Weights & Biases).
• Familiarity with Hugging Face ecosystem.
• Experience with large-scale data processing (Spark,Dask, or similar).
• Exposure to Kubernetes or other container orchestration platforms.
• Prior experience with monitoring/observability for ML systems.

Why Join Neural Nurture

At Neural Nurture, you will work alongside experienced researchers and engineers specializing in ML, NLP, and Computer Vision.Youllhave the opportunity to build systems that directly power AI products while staying close tocutting-edgeresearch. Our collaborative environment values engineering excellence and provides hands-on mentorship, helping you grow as an ML professional with experience spanning both research-driven and production-grade systems.

Compensation:

Base salary for this full-time position ranges from ?3L to ?5L, along with performance bonuses, equity, and benefits. Compensation isdeterminedbased onrole, level, and location. Individual pay within the range is influenced by factors such as work location, relevant skills, experience, and educational background.