AI/ML Engineer - NLP/Python

Job Opening : AI/ML Engineer

Location : Full Remote

Job Type : Full-Time

Salary Range : $3,000 $6,000 USD / month

Salary Range : 40 lakhs 70 lakh / month

Experience Level : Mid to Senior (35+ years)

About the Role :

We're seeking a versatile and innovative AI/ML Engineer to join our growing team. This role sits at the intersection of data science, machine learning, NLP, and software engineering. You'll be designing and deploying production-grade machine learning systems, experimenting with cutting-edge LLMs, and solving real-world problems using unsupervised learning, graph-based models, and distributed systems.

Youll collaborate cross-functionally with product managers, designers, and engineers to shape how we leverage AI across our platformsfrom education to healthcare.

Responsibilities :

- Design, prototype, train, and deploy LLMs and traditional ML models for :

- Semantic understanding, emotion detection, expressive summarization

- Text clustering, topic modeling, and classification

- Intent/sentiment extraction and entity resolution

- Recommendation systems and agentic RAG systems

- Develop clean, scalable ML pipelines and integrate them with existing systems using APIs and batch

services

- Collaborate with cross-functional teams to understand user needs and translate them into AI-powered solutions

- Manage full ML lifecycle : from data wrangling (SQL, pipelines) to model deployment (cloud-based environments)

- Build knowledge graphs and explore Graph Neural Networks (GNNs) for structured reasoning

- Experiment with new ML approaches and keep up with advances in modern NLP and distributed inference

- Monitor, evaluate, and continuously improve model performance in production

- Document solutions and communicate results clearly to both technical and non-technical stakeholders

Requirements : 35+ years of experience building and deploying ML systems (production experience a must)

Strong hands-on skills in :

- Python and SQL

- NLP libraries (Spacy, NLTK, HuggingFace, etc.)

- Deep learning frameworks (PyTorch, TensorFlow, JAX)

Working knowledge of :

- Modern NLP and LLM fine tuning

- Unsupervised techniques like clustering and topic modeling

- Semantic similarity, summarization, classification, sentiment/emotion detection

- Distributed training/inference and cloud infrastructure (AWS, Azure, or GCP)

Experience with :

- Microservices and API integrations

- Docker, Kubernetes, and containerized ML deployments

- MLOps practices : CI/CD for ML, model monitoring, and pipeline automation

- Familiarity with domain-driven design and scalable, decoupled architectures

- Strong communication and storytelling ability to tie technical work to product and business outcomes

Bonus Skills :

- Experience with graph-based ML (Knowledge Graphs, GNNs, DGL)

- Exposure to networked, multi-rank GPU environments

- Background in data engineering or DevOps

- Data visualization for ML explain ability and diagnostics

- Passion for education, healthcare, or social impact applications